# coding: utf-8
# (C) Copyright IBM Corp. 2015, 2021.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# IBM OpenAPI SDK Code Generator Version: 99-SNAPSHOT-902c9336-20210507-162723
"""
The IBM Watson™ Text to Speech service provides APIs that use IBM's speech-synthesis
capabilities to synthesize text into natural-sounding speech in a variety of languages,
dialects, and voices. The service supports at least one male or female voice, sometimes
both, for each language. The audio is streamed back to the client with minimal delay.
For speech synthesis, the service supports a synchronous HTTP Representational State
Transfer (REST) interface and a WebSocket interface. Both interfaces support plain text
and SSML input. SSML is an XML-based markup language that provides text annotation for
speech-synthesis applications. The WebSocket interface also supports the SSML
<code><mark></code> element and word timings.
The service offers a customization interface that you can use to define sounds-like or
phonetic translations for words. A sounds-like translation consists of one or more words
that, when combined, sound like the word. A phonetic translation is based on the SSML
phoneme format for representing a word. You can specify a phonetic translation in standard
International Phonetic Alphabet (IPA) representation or in the proprietary IBM Symbolic
Phonetic Representation (SPR). The Arabic, Chinese, Dutch, Australian English, and Korean
languages support only IPA.
The service also offers a Tune by Example feature that lets you define custom prompts. You
can also define speaker models to improve the quality of your custom prompts. The service
support custom prompts only for US English custom models and voices.
"""
from enum import Enum
from typing import BinaryIO, Dict, List
import json
from ibm_cloud_sdk_core import BaseService, DetailedResponse
from ibm_cloud_sdk_core.authenticators.authenticator import Authenticator
from ibm_cloud_sdk_core.get_authenticator import get_authenticator_from_environment
from ibm_cloud_sdk_core.utils import convert_model
from .common import get_sdk_headers
##############################################################################
# Service
##############################################################################
[docs]class TextToSpeechV1(BaseService):
"""The Text to Speech V1 service."""
DEFAULT_SERVICE_URL = 'https://api.us-south.text-to-speech.watson.cloud.ibm.com'
DEFAULT_SERVICE_NAME = 'text_to_speech'
def __init__(
self,
authenticator: Authenticator = None,
service_name: str = DEFAULT_SERVICE_NAME,
) -> None:
"""
Construct a new client for the Text to Speech service.
:param Authenticator authenticator: The authenticator specifies the authentication mechanism.
Get up to date information from https://github.com/IBM/python-sdk-core/blob/master/README.md
about initializing the authenticator of your choice.
"""
if not authenticator:
authenticator = get_authenticator_from_environment(service_name)
BaseService.__init__(self,
service_url=self.DEFAULT_SERVICE_URL,
authenticator=authenticator)
self.configure_service(service_name)
#########################
# Voices
#########################
[docs] def list_voices(self, **kwargs) -> DetailedResponse:
"""
List voices.
Lists all voices available for use with the service. The information includes the
name, language, gender, and other details about the voice. The ordering of the
list of voices can change from call to call; do not rely on an alphabetized or
static list of voices. To see information about a specific voice, use the **Get a
voice** method.
**See also:** [Listing all available
voices](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-voices#listVoices).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Voices` object
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_voices')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v1/voices'
request = self.prepare_request(method='GET', url=url, headers=headers)
response = self.send(request)
return response
[docs] def get_voice(self,
voice: str,
*,
customization_id: str = None,
**kwargs) -> DetailedResponse:
"""
Get a voice.
Gets information about the specified voice. The information includes the name,
language, gender, and other details about the voice. Specify a customization ID to
obtain information for a custom model that is defined for the language of the
specified voice. To list information about all available voices, use the **List
voices** method.
**See also:** [Listing a specific
voice](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-voices#listVoice).
### Important voice updates
The service's voices underwent significant change on 2 December 2020.
* The Arabic, Chinese, Dutch, Australian English, and Korean voices are now neural
instead of concatenative.
* The `ar-AR_OmarVoice` voice is deprecated. Use `ar-MS_OmarVoice` voice instead.
* The `ar-AR` language identifier cannot be used to create a custom model. Use the
`ar-MS` identifier instead.
* The standard concatenative voices for the following languages are now
deprecated: Brazilian Portuguese, United Kingdom and United States English,
French, German, Italian, Japanese, and Spanish (all dialects).
* The features expressive SSML, voice transformation SSML, and use of the `volume`
attribute of the `<prosody>` element are deprecated and are not supported with any
of the service's neural voices.
* All of the service's voices are now customizable and generally available (GA)
for production use.
The deprecated voices and features will continue to function for at least one year
but might be removed at a future date. You are encouraged to migrate to the
equivalent neural voices at your earliest convenience. For more information about
all voice updates, see the [2 December 2020 service
update](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-release-notes#December2020)
in the release notes.
:param str voice: The voice for which information is to be returned. For
more information about specifying a voice, see **Important voice updates**
in the method description.
:param str customization_id: (optional) The customization ID (GUID) of a
custom model for which information is to be returned. You must make the
request with credentials for the instance of the service that owns the
custom model. Omit the parameter to see information about the specified
voice with no customization.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Voice` object
"""
if voice is None:
raise ValueError('voice must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_voice')
headers.update(sdk_headers)
params = {'customization_id': customization_id}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['voice']
path_param_values = self.encode_path_vars(voice)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/voices/{voice}'.format(**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Synthesis
#########################
[docs] def synthesize(self,
text: str,
*,
accept: str = None,
voice: str = None,
customization_id: str = None,
**kwargs) -> DetailedResponse:
"""
Synthesize audio.
Synthesizes text to audio that is spoken in the specified voice. The service bases
its understanding of the language for the input text on the specified voice. Use a
voice that matches the language of the input text.
The method accepts a maximum of 5 KB of input text in the body of the request, and
8 KB for the URL and headers. The 5 KB limit includes any SSML tags that you
specify. The service returns the synthesized audio stream as an array of bytes.
**See also:** [The HTTP
interface](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-usingHTTP#usingHTTP).
### Audio formats (accept types)
The service can return audio in the following formats (MIME types).
* Where indicated, you can optionally specify the sampling rate (`rate`) of the
audio. You must specify a sampling rate for the `audio/l16` and `audio/mulaw`
formats. A specified sampling rate must lie in the range of 8 kHz to 192 kHz. Some
formats restrict the sampling rate to certain values, as noted.
* For the `audio/l16` format, you can optionally specify the endianness
(`endianness`) of the audio: `endianness=big-endian` or
`endianness=little-endian`.
Use the `Accept` header or the `accept` parameter to specify the requested format
of the response audio. If you omit an audio format altogether, the service returns
the audio in Ogg format with the Opus codec (`audio/ogg;codecs=opus`). The service
always returns single-channel audio.
* `audio/basic` - The service returns audio with a sampling rate of 8000 Hz.
* `audio/flac` - You can optionally specify the `rate` of the audio. The default
sampling rate is 22,050 Hz.
* `audio/l16` - You must specify the `rate` of the audio. You can optionally
specify the `endianness` of the audio. The default endianness is `little-endian`.
* `audio/mp3` - You can optionally specify the `rate` of the audio. The default
sampling rate is 22,050 Hz.
* `audio/mpeg` - You can optionally specify the `rate` of the audio. The default
sampling rate is 22,050 Hz.
* `audio/mulaw` - You must specify the `rate` of the audio.
* `audio/ogg` - The service returns the audio in the `vorbis` codec. You can
optionally specify the `rate` of the audio. The default sampling rate is 22,050
Hz.
* `audio/ogg;codecs=opus` - You can optionally specify the `rate` of the audio.
Only the following values are valid sampling rates: `48000`, `24000`, `16000`,
`12000`, or `8000`. If you specify a value other than one of these, the service
returns an error. The default sampling rate is 48,000 Hz.
* `audio/ogg;codecs=vorbis` - You can optionally specify the `rate` of the audio.
The default sampling rate is 22,050 Hz.
* `audio/wav` - You can optionally specify the `rate` of the audio. The default
sampling rate is 22,050 Hz.
* `audio/webm` - The service returns the audio in the `opus` codec. The service
returns audio with a sampling rate of 48,000 Hz.
* `audio/webm;codecs=opus` - The service returns audio with a sampling rate of
48,000 Hz.
* `audio/webm;codecs=vorbis` - You can optionally specify the `rate` of the audio.
The default sampling rate is 22,050 Hz.
For more information about specifying an audio format, including additional
details about some of the formats, see [Audio
formats](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-audioFormats#audioFormats).
### Important voice updates
The service's voices underwent significant change on 2 December 2020.
* The Arabic, Chinese, Dutch, Australian English, and Korean voices are now neural
instead of concatenative.
* The `ar-AR_OmarVoice` voice is deprecated. Use `ar-MS_OmarVoice` voice instead.
* The `ar-AR` language identifier cannot be used to create a custom model. Use the
`ar-MS` identifier instead.
* The standard concatenative voices for the following languages are now
deprecated: Brazilian Portuguese, United Kingdom and United States English,
French, German, Italian, Japanese, and Spanish (all dialects).
* The features expressive SSML, voice transformation SSML, and use of the `volume`
attribute of the `<prosody>` element are deprecated and are not supported with any
of the service's neural voices.
* All of the service's voices are now customizable and generally available (GA)
for production use.
The deprecated voices and features will continue to function for at least one year
but might be removed at a future date. You are encouraged to migrate to the
equivalent neural voices at your earliest convenience. For more information about
all voice updates, see the [2 December 2020 service
update](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-release-notes#December2020)
in the release notes.
### Warning messages
If a request includes invalid query parameters, the service returns a `Warnings`
response header that provides messages about the invalid parameters. The warning
includes a descriptive message and a list of invalid argument strings. For
example, a message such as `"Unknown arguments:"` or `"Unknown url query
arguments:"` followed by a list of the form `"{invalid_arg_1}, {invalid_arg_2}."`
The request succeeds despite the warnings.
:param str text: The text to synthesize.
:param str accept: (optional) The requested format (MIME type) of the
audio. You can use the `Accept` header or the `accept` parameter to specify
the audio format. For more information about specifying an audio format,
see **Audio formats (accept types)** in the method description.
:param str voice: (optional) The voice to use for synthesis. For more
information about specifying a voice, see **Important voice updates** in
the method description.
:param str customization_id: (optional) The customization ID (GUID) of a
custom model to use for the synthesis. If a custom model is specified, it
works only if it matches the language of the indicated voice. You must make
the request with credentials for the instance of the service that owns the
custom model. Omit the parameter to use the specified voice with no
customization.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `BinaryIO` result
"""
if text is None:
raise ValueError('text must be provided')
headers = {'Accept': accept}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='synthesize')
headers.update(sdk_headers)
params = {'voice': voice, 'customization_id': customization_id}
data = {'text': text}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v1/synthesize'
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
#########################
# Pronunciation
#########################
[docs] def get_pronunciation(self,
text: str,
*,
voice: str = None,
format: str = None,
customization_id: str = None,
**kwargs) -> DetailedResponse:
"""
Get pronunciation.
Gets the phonetic pronunciation for the specified word. You can request the
pronunciation for a specific format. You can also request the pronunciation for a
specific voice to see the default translation for the language of that voice or
for a specific custom model to see the translation for that model.
**See also:** [Querying a word from a
language](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customWords#cuWordsQueryLanguage).
### Important voice updates
The service's voices underwent significant change on 2 December 2020.
* The Arabic, Chinese, Dutch, Australian English, and Korean voices are now neural
instead of concatenative.
* The `ar-AR_OmarVoice` voice is deprecated. Use `ar-MS_OmarVoice` voice instead.
* The `ar-AR` language identifier cannot be used to create a custom model. Use the
`ar-MS` identifier instead.
* The standard concatenative voices for the following languages are now
deprecated: Brazilian Portuguese, United Kingdom and United States English,
French, German, Italian, Japanese, and Spanish (all dialects).
* The features expressive SSML, voice transformation SSML, and use of the `volume`
attribute of the `<prosody>` element are deprecated and are not supported with any
of the service's neural voices.
* All of the service's voices are now customizable and generally available (GA)
for production use.
The deprecated voices and features will continue to function for at least one year
but might be removed at a future date. You are encouraged to migrate to the
equivalent neural voices at your earliest convenience. For more information about
all voice updates, see the [2 December 2020 service
update](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-release-notes#December2020)
in the release notes.
:param str text: The word for which the pronunciation is requested.
:param str voice: (optional) A voice that specifies the language in which
the pronunciation is to be returned. All voices for the same language (for
example, `en-US`) return the same translation. For more information about
specifying a voice, see **Important voice updates** in the method
description.
:param str format: (optional) The phoneme format in which to return the
pronunciation. The Arabic, Chinese, Dutch, Australian English, and Korean
languages support only IPA. Omit the parameter to obtain the pronunciation
in the default format.
:param str customization_id: (optional) The customization ID (GUID) of a
custom model for which the pronunciation is to be returned. The language of
a specified custom model must match the language of the specified voice. If
the word is not defined in the specified custom model, the service returns
the default translation for the custom model's language. You must make the
request with credentials for the instance of the service that owns the
custom model. Omit the parameter to see the translation for the specified
voice with no customization.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Pronunciation` object
"""
if text is None:
raise ValueError('text must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_pronunciation')
headers.update(sdk_headers)
params = {
'text': text,
'voice': voice,
'format': format,
'customization_id': customization_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v1/pronunciation'
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Custom models
#########################
[docs] def create_custom_model(self,
name: str,
*,
language: str = None,
description: str = None,
**kwargs) -> DetailedResponse:
"""
Create a custom model.
Creates a new empty custom model. You must specify a name for the new custom
model. You can optionally specify the language and a description for the new
model. The model is owned by the instance of the service whose credentials are
used to create it.
**See also:** [Creating a custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customModels#cuModelsCreate).
### Important voice updates
The service's voices underwent significant change on 2 December 2020.
* The Arabic, Chinese, Dutch, Australian English, and Korean voices are now neural
instead of concatenative.
* The `ar-AR_OmarVoice` voice is deprecated. Use `ar-MS_OmarVoice` voice instead.
* The `ar-AR` language identifier cannot be used to create a custom model. Use the
`ar-MS` identifier instead.
* The standard concatenative voices for the following languages are now
deprecated: Brazilian Portuguese, United Kingdom and United States English,
French, German, Italian, Japanese, and Spanish (all dialects).
* The features expressive SSML, voice transformation SSML, and use of the `volume`
attribute of the `<prosody>` element are deprecated and are not supported with any
of the service's neural voices.
* All of the service's voices are now customizable and generally available (GA)
for production use.
The deprecated voices and features will continue to function for at least one year
but might be removed at a future date. You are encouraged to migrate to the
equivalent neural voices at your earliest convenience. For more information about
all voice updates, see the [2 December 2020 service
update](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-release-notes#December2020)
in the release notes.
:param str name: The name of the new custom model.
:param str language: (optional) The language of the new custom model. You
create a custom model for a specific language, not for a specific voice. A
custom model can be used with any voice for its specified language. Omit
the parameter to use the the default language, `en-US`. **Note:** The
`ar-AR` language identifier cannot be used to create a custom model. Use
the `ar-MS` identifier instead.
:param str description: (optional) A description of the new custom model.
Specifying a description is recommended.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `CustomModel` object
"""
if name is None:
raise ValueError('name must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='create_custom_model')
headers.update(sdk_headers)
data = {'name': name, 'language': language, 'description': description}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v1/customizations'
request = self.prepare_request(method='POST',
url=url,
headers=headers,
data=data)
response = self.send(request)
return response
[docs] def list_custom_models(self,
*,
language: str = None,
**kwargs) -> DetailedResponse:
"""
List custom models.
Lists metadata such as the name and description for all custom models that are
owned by an instance of the service. Specify a language to list the custom models
for that language only. To see the words and prompts in addition to the metadata
for a specific custom model, use the **Get a custom model** method. You must use
credentials for the instance of the service that owns a model to list information
about it.
**See also:** [Querying all custom
models](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customModels#cuModelsQueryAll).
:param str language: (optional) The language for which custom models that
are owned by the requesting credentials are to be returned. Omit the
parameter to see all custom models that are owned by the requester.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `CustomModels` object
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_custom_models')
headers.update(sdk_headers)
params = {'language': language}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v1/customizations'
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def update_custom_model(self,
customization_id: str,
*,
name: str = None,
description: str = None,
words: List['Word'] = None,
**kwargs) -> DetailedResponse:
"""
Update a custom model.
Updates information for the specified custom model. You can update metadata such
as the name and description of the model. You can also update the words in the
model and their translations. Adding a new translation for a word that already
exists in a custom model overwrites the word's existing translation. A custom
model can contain no more than 20,000 entries. You must use credentials for the
instance of the service that owns a model to update it.
You can define sounds-like or phonetic translations for words. A sounds-like
translation consists of one or more words that, when combined, sound like the
word. Phonetic translations are based on the SSML phoneme format for representing
a word. You can specify them in standard International Phonetic Alphabet (IPA)
representation
<code><phoneme alphabet="ipa"
ph="təmˈɑto"></phoneme></code>
or in the proprietary IBM Symbolic Phonetic Representation (SPR)
<code><phoneme alphabet="ibm"
ph="1gAstroEntxrYFXs"></phoneme></code>
**See also:**
* [Updating a custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customModels#cuModelsUpdate)
* [Adding words to a Japanese custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customWords#cuJapaneseAdd)
* [Understanding
customization](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customIntro#customIntro).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param str name: (optional) A new name for the custom model.
:param str description: (optional) A new description for the custom model.
:param List[Word] words: (optional) An array of `Word` objects that
provides the words and their translations that are to be added or updated
for the custom model. Pass an empty array to make no additions or updates.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
if words is not None:
words = [convert_model(x) for x in words]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='update_custom_model')
headers.update(sdk_headers)
data = {'name': name, 'description': description, 'words': words}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['customization_id']
path_param_values = self.encode_path_vars(customization_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}'.format(**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
data=data)
response = self.send(request)
return response
[docs] def get_custom_model(self, customization_id: str,
**kwargs) -> DetailedResponse:
"""
Get a custom model.
Gets all information about a specified custom model. In addition to metadata such
as the name and description of the custom model, the output includes the words and
their translations that are defined for the model, as well as any prompts that are
defined for the model. To see just the metadata for a model, use the **List custom
models** method.
**See also:** [Querying a custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customModels#cuModelsQuery).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `CustomModel` object
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_custom_model')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['customization_id']
path_param_values = self.encode_path_vars(customization_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}'.format(**path_param_dict)
request = self.prepare_request(method='GET', url=url, headers=headers)
response = self.send(request)
return response
[docs] def delete_custom_model(self, customization_id: str,
**kwargs) -> DetailedResponse:
"""
Delete a custom model.
Deletes the specified custom model. You must use credentials for the instance of
the service that owns a model to delete it.
**See also:** [Deleting a custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customModels#cuModelsDelete).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_custom_model')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
path_param_keys = ['customization_id']
path_param_values = self.encode_path_vars(customization_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}'.format(**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers)
response = self.send(request)
return response
#########################
# Custom words
#########################
[docs] def add_words(self, customization_id: str, words: List['Word'],
**kwargs) -> DetailedResponse:
"""
Add custom words.
Adds one or more words and their translations to the specified custom model.
Adding a new translation for a word that already exists in a custom model
overwrites the word's existing translation. A custom model can contain no more
than 20,000 entries. You must use credentials for the instance of the service that
owns a model to add words to it.
You can define sounds-like or phonetic translations for words. A sounds-like
translation consists of one or more words that, when combined, sound like the
word. Phonetic translations are based on the SSML phoneme format for representing
a word. You can specify them in standard International Phonetic Alphabet (IPA)
representation
<code><phoneme alphabet="ipa"
ph="təmˈɑto"></phoneme></code>
or in the proprietary IBM Symbolic Phonetic Representation (SPR)
<code><phoneme alphabet="ibm"
ph="1gAstroEntxrYFXs"></phoneme></code>
**See also:**
* [Adding multiple words to a custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customWords#cuWordsAdd)
* [Adding words to a Japanese custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customWords#cuJapaneseAdd)
* [Understanding
customization](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customIntro#customIntro).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param List[Word] words: The **Add custom words** method accepts an array
of `Word` objects. Each object provides a word that is to be added or
updated for the custom model and the word's translation.
The **List custom words** method returns an array of `Word` objects. Each
object shows a word and its translation from the custom model. The words
are listed in alphabetical order, with uppercase letters listed before
lowercase letters. The array is empty if the custom model contains no
words.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
if words is None:
raise ValueError('words must be provided')
words = [convert_model(x) for x in words]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='add_words')
headers.update(sdk_headers)
data = {'words': words}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['customization_id']
path_param_values = self.encode_path_vars(customization_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}/words'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
data=data)
response = self.send(request)
return response
[docs] def list_words(self, customization_id: str, **kwargs) -> DetailedResponse:
"""
List custom words.
Lists all of the words and their translations for the specified custom model. The
output shows the translations as they are defined in the model. You must use
credentials for the instance of the service that owns a model to list its words.
**See also:** [Querying all words from a custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customWords#cuWordsQueryModel).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Words` object
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_words')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['customization_id']
path_param_values = self.encode_path_vars(customization_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}/words'.format(
**path_param_dict)
request = self.prepare_request(method='GET', url=url, headers=headers)
response = self.send(request)
return response
[docs] def add_word(self,
customization_id: str,
word: str,
translation: str,
*,
part_of_speech: str = None,
**kwargs) -> DetailedResponse:
"""
Add a custom word.
Adds a single word and its translation to the specified custom model. Adding a new
translation for a word that already exists in a custom model overwrites the word's
existing translation. A custom model can contain no more than 20,000 entries. You
must use credentials for the instance of the service that owns a model to add a
word to it.
You can define sounds-like or phonetic translations for words. A sounds-like
translation consists of one or more words that, when combined, sound like the
word. Phonetic translations are based on the SSML phoneme format for representing
a word. You can specify them in standard International Phonetic Alphabet (IPA)
representation
<code><phoneme alphabet="ipa"
ph="təmˈɑto"></phoneme></code>
or in the proprietary IBM Symbolic Phonetic Representation (SPR)
<code><phoneme alphabet="ibm"
ph="1gAstroEntxrYFXs"></phoneme></code>
**See also:**
* [Adding a single word to a custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customWords#cuWordAdd)
* [Adding words to a Japanese custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customWords#cuJapaneseAdd)
* [Understanding
customization](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customIntro#customIntro).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param str word: The word that is to be added or updated for the custom
model.
:param str translation: The phonetic or sounds-like translation for the
word. A phonetic translation is based on the SSML format for representing
the phonetic string of a word either as an IPA translation or as an IBM SPR
translation. The Arabic, Chinese, Dutch, Australian English, and Korean
languages support only IPA. A sounds-like is one or more words that, when
combined, sound like the word.
:param str part_of_speech: (optional) **Japanese only.** The part of speech
for the word. The service uses the value to produce the correct intonation
for the word. You can create only a single entry, with or without a single
part of speech, for any word; you cannot create multiple entries with
different parts of speech for the same word. For more information, see
[Working with Japanese
entries](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-rules#jaNotes).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
if word is None:
raise ValueError('word must be provided')
if translation is None:
raise ValueError('translation must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='add_word')
headers.update(sdk_headers)
data = {'translation': translation, 'part_of_speech': part_of_speech}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
path_param_keys = ['customization_id', 'word']
path_param_values = self.encode_path_vars(customization_id, word)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}/words/{word}'.format(
**path_param_dict)
request = self.prepare_request(method='PUT',
url=url,
headers=headers,
data=data)
response = self.send(request)
return response
[docs] def get_word(self, customization_id: str, word: str,
**kwargs) -> DetailedResponse:
"""
Get a custom word.
Gets the translation for a single word from the specified custom model. The output
shows the translation as it is defined in the model. You must use credentials for
the instance of the service that owns a model to list its words.
**See also:** [Querying a single word from a custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customWords#cuWordQueryModel).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param str word: The word that is to be queried from the custom model.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Translation` object
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
if word is None:
raise ValueError('word must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_word')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['customization_id', 'word']
path_param_values = self.encode_path_vars(customization_id, word)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}/words/{word}'.format(
**path_param_dict)
request = self.prepare_request(method='GET', url=url, headers=headers)
response = self.send(request)
return response
[docs] def delete_word(self, customization_id: str, word: str,
**kwargs) -> DetailedResponse:
"""
Delete a custom word.
Deletes a single word from the specified custom model. You must use credentials
for the instance of the service that owns a model to delete its words.
**See also:** [Deleting a word from a custom
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customWords#cuWordDelete).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param str word: The word that is to be deleted from the custom model.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
if word is None:
raise ValueError('word must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_word')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
path_param_keys = ['customization_id', 'word']
path_param_values = self.encode_path_vars(customization_id, word)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}/words/{word}'.format(
**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers)
response = self.send(request)
return response
#########################
# Custom prompts
#########################
[docs] def list_custom_prompts(self, customization_id: str,
**kwargs) -> DetailedResponse:
"""
List custom prompts.
Lists information about all custom prompts that are defined for a custom model.
The information includes the prompt ID, prompt text, status, and optional speaker
ID for each prompt of the custom model. You must use credentials for the instance
of the service that owns the custom model. The same information about all of the
prompts for a custom model is also provided by the **Get a custom model** method.
That method provides complete details about a specified custom model, including
its language, owner, custom words, and more.
**Beta:** Custom prompts are beta functionality that is supported only for use
with US English custom models and voices.
**See also:** [Listing custom
prompts](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-custom-prompts#tbe-custom-prompts-list).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Prompts` object
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_custom_prompts')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['customization_id']
path_param_values = self.encode_path_vars(customization_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}/prompts'.format(
**path_param_dict)
request = self.prepare_request(method='GET', url=url, headers=headers)
response = self.send(request)
return response
[docs] def add_custom_prompt(self, customization_id: str, prompt_id: str,
metadata: 'PromptMetadata', file: BinaryIO,
**kwargs) -> DetailedResponse:
"""
Add a custom prompt.
Adds a custom prompt to a custom model. A prompt is defined by the text that is to
be spoken, the audio for that text, a unique user-specified ID for the prompt, and
an optional speaker ID. The information is used to generate prosodic data that is
not visible to the user. This data is used by the service to produce the
synthesized audio upon request. You must use credentials for the instance of the
service that owns a custom model to add a prompt to it. You can add a maximum of
1000 custom prompts to a single custom model.
You are recommended to assign meaningful values for prompt IDs. For example, use
`goodbye` to identify a prompt that speaks a farewell message. Prompt IDs must be
unique within a given custom model. You cannot define two prompts with the same
name for the same custom model. If you provide the ID of an existing prompt, the
previously uploaded prompt is replaced by the new information. The existing prompt
is reprocessed by using the new text and audio and, if provided, new speaker
model, and the prosody data associated with the prompt is updated.
The quality of a prompt is undefined if the language of a prompt does not match
the language of its custom model. This is consistent with any text or SSML that is
specified for a speech synthesis request. The service makes a best-effort attempt
to render the specified text for the prompt; it does not validate that the
language of the text matches the language of the model.
Adding a prompt is an asynchronous operation. Although it accepts less audio than
speaker enrollment, the service must align the audio with the provided text. The
time that it takes to process a prompt depends on the prompt itself. The
processing time for a reasonably sized prompt generally matches the length of the
audio (for example, it takes 20 seconds to process a 20-second prompt).
For shorter prompts, you can wait for a reasonable amount of time and then check
the status of the prompt with the **Get a custom prompt** method. For longer
prompts, consider using that method to poll the service every few seconds to
determine when the prompt becomes available. No prompt can be used for speech
synthesis if it is in the `processing` or `failed` state. Only prompts that are in
the `available` state can be used for speech synthesis.
When it processes a request, the service attempts to align the text and the audio
that are provided for the prompt. The text that is passed with a prompt must match
the spoken audio as closely as possible. Optimally, the text and audio match
exactly. The service does its best to align the specified text with the audio, and
it can often compensate for mismatches between the two. But if the service cannot
effectively align the text and the audio, possibly because the magnitude of
mismatches between the two is too great, processing of the prompt fails.
### Evaluating a prompt
Always listen to and evaluate a prompt to determine its quality before using it
in production. To evaluate a prompt, include only the single prompt in a speech
synthesis request by using the following SSML extension, in this case for a prompt
whose ID is `goodbye`:
`<ibm:prompt id="goodbye"/>`
In some cases, you might need to rerecord and resubmit a prompt as many as five
times to address the following possible problems:
* The service might fail to detect a mismatch between the prompt’s text and audio.
The longer the prompt, the greater the chance for misalignment between its text
and audio. Therefore, multiple shorter prompts are preferable to a single long
prompt.
* The text of a prompt might include a word that the service does not recognize.
In this case, you can create a custom word and pronunciation pair to tell the
service how to pronounce the word. You must then re-create the prompt.
* The quality of the input audio might be insufficient or the service’s processing
of the audio might fail to detect the intended prosody. Submitting new audio for
the prompt can correct these issues.
If a prompt that is created without a speaker ID does not adequately reflect the
intended prosody, enrolling the speaker and providing a speaker ID for the prompt
is one recommended means of potentially improving the quality of the prompt. This
is especially important for shorter prompts such as "good-bye" or "thank you,"
where less audio data makes it more difficult to match the prosody of the speaker.
**Beta:** Custom prompts are beta functionality that is supported only for use
with US English custom models and voices.
**See also:**
* [Add a custom
prompt](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-create#tbe-create-add-prompt)
* [Evaluate a custom
prompt](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-create#tbe-create-evaluate-prompt)
* [Rules for creating custom
prompts](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-rules#tbe-rules-prompts).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param str prompt_id: The identifier of the prompt that is to be added to
the custom model:
* Include a maximum of 49 characters in the ID.
* Include only alphanumeric characters and `_` (underscores) in the ID.
* Do not include XML sensitive characters (double quotes, single quotes,
ampersands, angle brackets, and slashes) in the ID.
* To add a new prompt, the ID must be unique for the specified custom
model. Otherwise, the new information for the prompt overwrites the
existing prompt that has that ID.
:param PromptMetadata metadata: Information about the prompt that is to be
added to a custom model. The following example of a `PromptMetadata` object
includes both the required prompt text and an optional speaker model ID:
`{ "prompt_text": "Thank you and good-bye!", "speaker_id":
"823068b2-ed4e-11ea-b6e0-7b6456aa95cc" }`.
:param BinaryIO file: An audio file that speaks the text of the prompt with
intonation and prosody that matches how you would like the prompt to be
spoken.
* The prompt audio must be in WAV format and must have a minimum sampling
rate of 16 kHz. The service accepts audio with higher sampling rates. The
service transcodes all audio to 16 kHz before processing it.
* The length of the prompt audio is limited to 30 seconds.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Prompt` object
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
if prompt_id is None:
raise ValueError('prompt_id must be provided')
if metadata is None:
raise ValueError('metadata must be provided')
if file is None:
raise ValueError('file must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='add_custom_prompt')
headers.update(sdk_headers)
form_data = []
form_data.append(
('metadata', (None, json.dumps(metadata), 'application/json')))
form_data.append(('file', (None, file, 'audio/wav')))
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['customization_id', 'prompt_id']
path_param_values = self.encode_path_vars(customization_id, prompt_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}/prompts/{prompt_id}'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
files=form_data)
response = self.send(request)
return response
[docs] def get_custom_prompt(self, customization_id: str, prompt_id: str,
**kwargs) -> DetailedResponse:
"""
Get a custom prompt.
Gets information about a specified custom prompt for a specified custom model. The
information includes the prompt ID, prompt text, status, and optional speaker ID
for each prompt of the custom model. You must use credentials for the instance of
the service that owns the custom model.
**Beta:** Custom prompts are beta functionality that is supported only for use
with US English custom models and voices.
**See also:** [Listing custom
prompts](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-custom-prompts#tbe-custom-prompts-list).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param str prompt_id: The identifier (name) of the prompt.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Prompt` object
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
if prompt_id is None:
raise ValueError('prompt_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_custom_prompt')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['customization_id', 'prompt_id']
path_param_values = self.encode_path_vars(customization_id, prompt_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}/prompts/{prompt_id}'.format(
**path_param_dict)
request = self.prepare_request(method='GET', url=url, headers=headers)
response = self.send(request)
return response
[docs] def delete_custom_prompt(self, customization_id: str, prompt_id: str,
**kwargs) -> DetailedResponse:
"""
Delete a custom prompt.
Deletes an existing custom prompt from a custom model. The service deletes the
prompt with the specified ID. You must use credentials for the instance of the
service that owns the custom model from which the prompt is to be deleted.
**Caution:** Deleting a custom prompt elicits a 400 response code from synthesis
requests that attempt to use the prompt. Make sure that you do not attempt to use
a deleted prompt in a production application.
**Beta:** Custom prompts are beta functionality that is supported only for use
with US English custom models and voices.
**See also:** [Deleting a custom
prompt](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-custom-prompts#tbe-custom-prompts-delete).
:param str customization_id: The customization ID (GUID) of the custom
model. You must make the request with credentials for the instance of the
service that owns the custom model.
:param str prompt_id: The identifier (name) of the prompt that is to be
deleted.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if customization_id is None:
raise ValueError('customization_id must be provided')
if prompt_id is None:
raise ValueError('prompt_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_custom_prompt')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
path_param_keys = ['customization_id', 'prompt_id']
path_param_values = self.encode_path_vars(customization_id, prompt_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/customizations/{customization_id}/prompts/{prompt_id}'.format(
**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers)
response = self.send(request)
return response
#########################
# Speaker models
#########################
[docs] def list_speaker_models(self, **kwargs) -> DetailedResponse:
"""
List speaker models.
Lists information about all speaker models that are defined for a service
instance. The information includes the speaker ID and speaker name of each defined
speaker. You must use credentials for the instance of a service to list its
speakers.
**Beta:** Speaker models and the custom prompts with which they are used are beta
functionality that is supported only for use with US English custom models and
voices.
**See also:** [Listing speaker
models](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-speaker-models#tbe-speaker-models-list).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Speakers` object
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_speaker_models')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v1/speakers'
request = self.prepare_request(method='GET', url=url, headers=headers)
response = self.send(request)
return response
[docs] def create_speaker_model(self, speaker_name: str, audio: BinaryIO,
**kwargs) -> DetailedResponse:
"""
Create a speaker model.
Creates a new speaker model, which is an optional enrollment token for users who
are to add prompts to custom models. A speaker model contains information about a
user's voice. The service extracts this information from a WAV audio sample that
you pass as the body of the request. Associating a speaker model with a prompt is
optional, but the information that is extracted from the speaker model helps the
service learn about the speaker's voice.
A speaker model can make an appreciable difference in the quality of prompts,
especially short prompts with relatively little audio, that are associated with
that speaker. A speaker model can help the service produce a prompt with more
confidence; the lack of a speaker model can potentially compromise the quality of
a prompt.
The gender of the speaker who creates a speaker model does not need to match the
gender of a voice that is used with prompts that are associated with that speaker
model. For example, a speaker model that is created by a male speaker can be
associated with prompts that are spoken by female voices.
You create a speaker model for a given instance of the service. The new speaker
model is owned by the service instance whose credentials are used to create it.
That same speaker can then be used to create prompts for all custom models within
that service instance. No language is associated with a speaker model, but each
custom model has a single specified language. You can add prompts only to US
English models.
You specify a name for the speaker when you create it. The name must be unique
among all speaker names for the owning service instance. To re-create a speaker
model for an existing speaker name, you must first delete the existing speaker
model that has that name.
Speaker enrollment is a synchronous operation. Although it accepts more audio data
than a prompt, the process of adding a speaker is very fast. The service simply
extracts information about the speaker’s voice from the audio. Unlike prompts,
speaker models neither need nor accept a transcription of the audio. When the call
returns, the audio is fully processed and the speaker enrollment is complete.
The service returns a speaker ID with the request. A speaker ID is globally unique
identifier (GUID) that you use to identify the speaker in subsequent requests to
the service.
**Beta:** Speaker models and the custom prompts with which they are used are beta
functionality that is supported only for use with US English custom models and
voices.
**See also:**
* [Create a speaker
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-create#tbe-create-speaker-model)
* [Rules for creating speaker
models](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-rules#tbe-rules-speakers).
:param str speaker_name: The name of the speaker that is to be added to the
service instance.
* Include a maximum of 49 characters in the name.
* Include only alphanumeric characters and `_` (underscores) in the name.
* Do not include XML sensitive characters (double quotes, single quotes,
ampersands, angle brackets, and slashes) in the name.
* Do not use the name of an existing speaker that is already defined for
the service instance.
:param BinaryIO audio: An enrollment audio file that contains a sample of
the speaker’s voice.
* The enrollment audio must be in WAV format and must have a minimum
sampling rate of 16 kHz. The service accepts audio with higher sampling
rates. It transcodes all audio to 16 kHz before processing it.
* The length of the enrollment audio is limited to 1 minute. Speaking one
or two paragraphs of text that include five to ten sentences is
recommended.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `SpeakerModel` object
"""
if speaker_name is None:
raise ValueError('speaker_name must be provided')
if audio is None:
raise ValueError('audio must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='create_speaker_model')
headers.update(sdk_headers)
params = {'speaker_name': speaker_name}
data = audio
headers['content-type'] = 'audio/wav'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v1/speakers'
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def get_speaker_model(self, speaker_id: str, **kwargs) -> DetailedResponse:
"""
Get a speaker model.
Gets information about all prompts that are defined by a specified speaker for all
custom models that are owned by a service instance. The information is grouped by
the customization IDs of the custom models. For each custom model, the information
lists information about each prompt that is defined for that custom model by the
speaker. You must use credentials for the instance of the service that owns a
speaker model to list its prompts.
**Beta:** Speaker models and the custom prompts with which they are used are beta
functionality that is supported only for use with US English custom models and
voices.
**See also:** [Listing the custom prompts for a speaker
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-speaker-models#tbe-speaker-models-list-prompts).
:param str speaker_id: The speaker ID (GUID) of the speaker model. You must
make the request with service credentials for the instance of the service
that owns the speaker model.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `SpeakerCustomModels` object
"""
if speaker_id is None:
raise ValueError('speaker_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_speaker_model')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['speaker_id']
path_param_values = self.encode_path_vars(speaker_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/speakers/{speaker_id}'.format(**path_param_dict)
request = self.prepare_request(method='GET', url=url, headers=headers)
response = self.send(request)
return response
[docs] def delete_speaker_model(self, speaker_id: str,
**kwargs) -> DetailedResponse:
"""
Delete a speaker model.
Deletes an existing speaker model from the service instance. The service deletes
the enrolled speaker with the specified speaker ID. You must use credentials for
the instance of the service that owns a speaker model to delete the speaker.
Any prompts that are associated with the deleted speaker are not affected by the
speaker's deletion. The prosodic data that defines the quality of a prompt is
established when the prompt is created. A prompt is static and remains unaffected
by deletion of its associated speaker. However, the prompt cannot be resubmitted
or updated with its original speaker once that speaker is deleted.
**Beta:** Speaker models and the custom prompts with which they are used are beta
functionality that is supported only for use with US English custom models and
voices.
**See also:** [Deleting a speaker
model](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-tbe-speaker-models#tbe-speaker-models-delete).
:param str speaker_id: The speaker ID (GUID) of the speaker model. You must
make the request with service credentials for the instance of the service
that owns the speaker model.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if speaker_id is None:
raise ValueError('speaker_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_speaker_model')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
path_param_keys = ['speaker_id']
path_param_values = self.encode_path_vars(speaker_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/speakers/{speaker_id}'.format(**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers)
response = self.send(request)
return response
#########################
# User data
#########################
[docs] def delete_user_data(self, customer_id: str, **kwargs) -> DetailedResponse:
"""
Delete labeled data.
Deletes all data that is associated with a specified customer ID. The method
deletes all data for the customer ID, regardless of the method by which the
information was added. The method has no effect if no data is associated with the
customer ID. You must issue the request with credentials for the same instance of
the service that was used to associate the customer ID with the data. You
associate a customer ID with data by passing the `X-Watson-Metadata` header with a
request that passes the data.
**Note:** If you delete an instance of the service from the service console, all
data associated with that service instance is automatically deleted. This includes
all custom models and word/translation pairs, and all data related to speech
synthesis requests.
**See also:** [Information
security](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-information-security#information-security).
:param str customer_id: The customer ID for which all data is to be
deleted.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if customer_id is None:
raise ValueError('customer_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_user_data')
headers.update(sdk_headers)
params = {'customer_id': customer_id}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v1/user_data'
request = self.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs]class GetVoiceEnums:
"""
Enums for get_voice parameters.
"""
[docs] class Voice(str, Enum):
"""
The voice for which information is to be returned. For more information about
specifying a voice, see **Important voice updates** in the method description.
"""
AR_AR_OMARVOICE = 'ar-AR_OmarVoice'
AR_MS_OMARVOICE = 'ar-MS_OmarVoice'
DE_DE_BIRGITVOICE = 'de-DE_BirgitVoice'
DE_DE_BIRGITV3VOICE = 'de-DE_BirgitV3Voice'
DE_DE_DIETERVOICE = 'de-DE_DieterVoice'
DE_DE_DIETERV3VOICE = 'de-DE_DieterV3Voice'
DE_DE_ERIKAV3VOICE = 'de-DE_ErikaV3Voice'
EN_AU_CRAIGVOICE = 'en-AU-CraigVoice'
EN_AU_MADISONVOICE = 'en-AU-MadisonVoice'
EN_GB_CHARLOTTEV3VOICE = 'en-GB_CharlotteV3Voice'
EN_GB_JAMESV3VOICE = 'en-GB_JamesV3Voice'
EN_GB_KATEVOICE = 'en-GB_KateVoice'
EN_GB_KATEV3VOICE = 'en-GB_KateV3Voice'
EN_US_ALLISONVOICE = 'en-US_AllisonVoice'
EN_US_ALLISONV3VOICE = 'en-US_AllisonV3Voice'
EN_US_EMILYV3VOICE = 'en-US_EmilyV3Voice'
EN_US_HENRYV3VOICE = 'en-US_HenryV3Voice'
EN_US_KEVINV3VOICE = 'en-US_KevinV3Voice'
EN_US_LISAVOICE = 'en-US_LisaVoice'
EN_US_LISAV3VOICE = 'en-US_LisaV3Voice'
EN_US_MICHAELVOICE = 'en-US_MichaelVoice'
EN_US_MICHAELV3VOICE = 'en-US_MichaelV3Voice'
EN_US_OLIVIAV3VOICE = 'en-US_OliviaV3Voice'
ES_ES_ENRIQUEVOICE = 'es-ES_EnriqueVoice'
ES_ES_ENRIQUEV3VOICE = 'es-ES_EnriqueV3Voice'
ES_ES_LAURAVOICE = 'es-ES_LauraVoice'
ES_ES_LAURAV3VOICE = 'es-ES_LauraV3Voice'
ES_LA_SOFIAVOICE = 'es-LA_SofiaVoice'
ES_LA_SOFIAV3VOICE = 'es-LA_SofiaV3Voice'
ES_US_SOFIAVOICE = 'es-US_SofiaVoice'
ES_US_SOFIAV3VOICE = 'es-US_SofiaV3Voice'
FR_CA_LOUISEV3VOICE = 'fr-CA_LouiseV3Voice'
FR_FR_NICOLASV3VOICE = 'fr-FR_NicolasV3Voice'
FR_FR_RENEEVOICE = 'fr-FR_ReneeVoice'
FR_FR_RENEEV3VOICE = 'fr-FR_ReneeV3Voice'
IT_IT_FRANCESCAVOICE = 'it-IT_FrancescaVoice'
IT_IT_FRANCESCAV3VOICE = 'it-IT_FrancescaV3Voice'
JA_JP_EMIVOICE = 'ja-JP_EmiVoice'
JA_JP_EMIV3VOICE = 'ja-JP_EmiV3Voice'
KO_KR_HYUNJUNVOICE = 'ko-KR_HyunjunVoice'
KO_KR_SIWOOVOICE = 'ko-KR_SiWooVoice'
KO_KR_YOUNGMIVOICE = 'ko-KR_YoungmiVoice'
KO_KR_YUNAVOICE = 'ko-KR_YunaVoice'
NL_NL_EMMAVOICE = 'nl-NL_EmmaVoice'
NL_NL_LIAMVOICE = 'nl-NL_LiamVoice'
PT_BR_ISABELAVOICE = 'pt-BR_IsabelaVoice'
PT_BR_ISABELAV3VOICE = 'pt-BR_IsabelaV3Voice'
ZH_CN_LINAVOICE = 'zh-CN_LiNaVoice'
ZH_CN_WANGWEIVOICE = 'zh-CN_WangWeiVoice'
ZH_CN_ZHANGJINGVOICE = 'zh-CN_ZhangJingVoice'
[docs]class SynthesizeEnums:
"""
Enums for synthesize parameters.
"""
[docs] class Accept(str, Enum):
"""
The requested format (MIME type) of the audio. You can use the `Accept` header or
the `accept` parameter to specify the audio format. For more information about
specifying an audio format, see **Audio formats (accept types)** in the method
description.
"""
AUDIO_BASIC = 'audio/basic'
AUDIO_FLAC = 'audio/flac'
AUDIO_L16 = 'audio/l16'
AUDIO_OGG = 'audio/ogg'
AUDIO_OGG_CODECS_OPUS = 'audio/ogg;codecs=opus'
AUDIO_OGG_CODECS_VORBIS = 'audio/ogg;codecs=vorbis'
AUDIO_MP3 = 'audio/mp3'
AUDIO_MPEG = 'audio/mpeg'
AUDIO_MULAW = 'audio/mulaw'
AUDIO_WAV = 'audio/wav'
AUDIO_WEBM = 'audio/webm'
AUDIO_WEBM_CODECS_OPUS = 'audio/webm;codecs=opus'
AUDIO_WEBM_CODECS_VORBIS = 'audio/webm;codecs=vorbis'
[docs] class Voice(str, Enum):
"""
The voice to use for synthesis. For more information about specifying a voice, see
**Important voice updates** in the method description.
"""
AR_AR_OMARVOICE = 'ar-AR_OmarVoice'
AR_MS_OMARVOICE = 'ar-MS_OmarVoice'
DE_DE_BIRGITVOICE = 'de-DE_BirgitVoice'
DE_DE_BIRGITV3VOICE = 'de-DE_BirgitV3Voice'
DE_DE_DIETERVOICE = 'de-DE_DieterVoice'
DE_DE_DIETERV3VOICE = 'de-DE_DieterV3Voice'
DE_DE_ERIKAV3VOICE = 'de-DE_ErikaV3Voice'
EN_AU_CRAIGVOICE = 'en-AU-CraigVoice'
EN_AU_MADISONVOICE = 'en-AU-MadisonVoice'
EN_GB_CHARLOTTEV3VOICE = 'en-GB_CharlotteV3Voice'
EN_GB_JAMESV3VOICE = 'en-GB_JamesV3Voice'
EN_GB_KATEVOICE = 'en-GB_KateVoice'
EN_GB_KATEV3VOICE = 'en-GB_KateV3Voice'
EN_US_ALLISONVOICE = 'en-US_AllisonVoice'
EN_US_ALLISONV3VOICE = 'en-US_AllisonV3Voice'
EN_US_EMILYV3VOICE = 'en-US_EmilyV3Voice'
EN_US_HENRYV3VOICE = 'en-US_HenryV3Voice'
EN_US_KEVINV3VOICE = 'en-US_KevinV3Voice'
EN_US_LISAVOICE = 'en-US_LisaVoice'
EN_US_LISAV3VOICE = 'en-US_LisaV3Voice'
EN_US_MICHAELVOICE = 'en-US_MichaelVoice'
EN_US_MICHAELV3VOICE = 'en-US_MichaelV3Voice'
EN_US_OLIVIAV3VOICE = 'en-US_OliviaV3Voice'
ES_ES_ENRIQUEVOICE = 'es-ES_EnriqueVoice'
ES_ES_ENRIQUEV3VOICE = 'es-ES_EnriqueV3Voice'
ES_ES_LAURAVOICE = 'es-ES_LauraVoice'
ES_ES_LAURAV3VOICE = 'es-ES_LauraV3Voice'
ES_LA_SOFIAVOICE = 'es-LA_SofiaVoice'
ES_LA_SOFIAV3VOICE = 'es-LA_SofiaV3Voice'
ES_US_SOFIAVOICE = 'es-US_SofiaVoice'
ES_US_SOFIAV3VOICE = 'es-US_SofiaV3Voice'
FR_CA_LOUISEV3VOICE = 'fr-CA_LouiseV3Voice'
FR_FR_NICOLASV3VOICE = 'fr-FR_NicolasV3Voice'
FR_FR_RENEEVOICE = 'fr-FR_ReneeVoice'
FR_FR_RENEEV3VOICE = 'fr-FR_ReneeV3Voice'
IT_IT_FRANCESCAVOICE = 'it-IT_FrancescaVoice'
IT_IT_FRANCESCAV3VOICE = 'it-IT_FrancescaV3Voice'
JA_JP_EMIVOICE = 'ja-JP_EmiVoice'
JA_JP_EMIV3VOICE = 'ja-JP_EmiV3Voice'
KO_KR_HYUNJUNVOICE = 'ko-KR_HyunjunVoice'
KO_KR_SIWOOVOICE = 'ko-KR_SiWooVoice'
KO_KR_YOUNGMIVOICE = 'ko-KR_YoungmiVoice'
KO_KR_YUNAVOICE = 'ko-KR_YunaVoice'
NL_NL_EMMAVOICE = 'nl-NL_EmmaVoice'
NL_NL_LIAMVOICE = 'nl-NL_LiamVoice'
PT_BR_ISABELAVOICE = 'pt-BR_IsabelaVoice'
PT_BR_ISABELAV3VOICE = 'pt-BR_IsabelaV3Voice'
ZH_CN_LINAVOICE = 'zh-CN_LiNaVoice'
ZH_CN_WANGWEIVOICE = 'zh-CN_WangWeiVoice'
ZH_CN_ZHANGJINGVOICE = 'zh-CN_ZhangJingVoice'
[docs]class GetPronunciationEnums:
"""
Enums for get_pronunciation parameters.
"""
[docs] class Voice(str, Enum):
"""
A voice that specifies the language in which the pronunciation is to be returned.
All voices for the same language (for example, `en-US`) return the same
translation. For more information about specifying a voice, see **Important voice
updates** in the method description.
"""
AR_AR_OMARVOICE = 'ar-AR_OmarVoice'
AR_MS_OMARVOICE = 'ar-MS_OmarVoice'
DE_DE_BIRGITVOICE = 'de-DE_BirgitVoice'
DE_DE_BIRGITV3VOICE = 'de-DE_BirgitV3Voice'
DE_DE_DIETERVOICE = 'de-DE_DieterVoice'
DE_DE_DIETERV3VOICE = 'de-DE_DieterV3Voice'
DE_DE_ERIKAV3VOICE = 'de-DE_ErikaV3Voice'
EN_AU_CRAIGVOICE = 'en-AU-CraigVoice'
EN_AU_MADISONVOICE = 'en-AU-MadisonVoice'
EN_GB_CHARLOTTEV3VOICE = 'en-GB_CharlotteV3Voice'
EN_GB_JAMESV3VOICE = 'en-GB_JamesV3Voice'
EN_GB_KATEVOICE = 'en-GB_KateVoice'
EN_GB_KATEV3VOICE = 'en-GB_KateV3Voice'
EN_US_ALLISONVOICE = 'en-US_AllisonVoice'
EN_US_ALLISONV3VOICE = 'en-US_AllisonV3Voice'
EN_US_EMILYV3VOICE = 'en-US_EmilyV3Voice'
EN_US_HENRYV3VOICE = 'en-US_HenryV3Voice'
EN_US_KEVINV3VOICE = 'en-US_KevinV3Voice'
EN_US_LISAVOICE = 'en-US_LisaVoice'
EN_US_LISAV3VOICE = 'en-US_LisaV3Voice'
EN_US_MICHAELVOICE = 'en-US_MichaelVoice'
EN_US_MICHAELV3VOICE = 'en-US_MichaelV3Voice'
EN_US_OLIVIAV3VOICE = 'en-US_OliviaV3Voice'
ES_ES_ENRIQUEVOICE = 'es-ES_EnriqueVoice'
ES_ES_ENRIQUEV3VOICE = 'es-ES_EnriqueV3Voice'
ES_ES_LAURAVOICE = 'es-ES_LauraVoice'
ES_ES_LAURAV3VOICE = 'es-ES_LauraV3Voice'
ES_LA_SOFIAVOICE = 'es-LA_SofiaVoice'
ES_LA_SOFIAV3VOICE = 'es-LA_SofiaV3Voice'
ES_US_SOFIAVOICE = 'es-US_SofiaVoice'
ES_US_SOFIAV3VOICE = 'es-US_SofiaV3Voice'
FR_CA_LOUISEV3VOICE = 'fr-CA_LouiseV3Voice'
FR_FR_NICOLASV3VOICE = 'fr-FR_NicolasV3Voice'
FR_FR_RENEEVOICE = 'fr-FR_ReneeVoice'
FR_FR_RENEEV3VOICE = 'fr-FR_ReneeV3Voice'
IT_IT_FRANCESCAVOICE = 'it-IT_FrancescaVoice'
IT_IT_FRANCESCAV3VOICE = 'it-IT_FrancescaV3Voice'
JA_JP_EMIVOICE = 'ja-JP_EmiVoice'
JA_JP_EMIV3VOICE = 'ja-JP_EmiV3Voice'
KO_KR_HYUNJUNVOICE = 'ko-KR_HyunjunVoice'
KO_KR_SIWOOVOICE = 'ko-KR_SiWooVoice'
KO_KR_YOUNGMIVOICE = 'ko-KR_YoungmiVoice'
KO_KR_YUNAVOICE = 'ko-KR_YunaVoice'
NL_NL_EMMAVOICE = 'nl-NL_EmmaVoice'
NL_NL_LIAMVOICE = 'nl-NL_LiamVoice'
PT_BR_ISABELAVOICE = 'pt-BR_IsabelaVoice'
PT_BR_ISABELAV3VOICE = 'pt-BR_IsabelaV3Voice'
ZH_CN_LINAVOICE = 'zh-CN_LiNaVoice'
ZH_CN_WANGWEIVOICE = 'zh-CN_WangWeiVoice'
ZH_CN_ZHANGJINGVOICE = 'zh-CN_ZhangJingVoice'
[docs]class ListCustomModelsEnums:
"""
Enums for list_custom_models parameters.
"""
[docs] class Language(str, Enum):
"""
The language for which custom models that are owned by the requesting credentials
are to be returned. Omit the parameter to see all custom models that are owned by
the requester.
"""
AR_MS = 'ar-MS'
DE_DE = 'de-DE'
EN_AU = 'en-AU'
EN_GB = 'en-GB'
EN_US = 'en-US'
ES_ES = 'es-ES'
ES_LA = 'es-LA'
ES_US = 'es-US'
FR_CA = 'fr-CA'
FR_FR = 'fr-FR'
IT_IT = 'it-IT'
JA_JP = 'ja-JP'
KO_KR = 'ko-KR'
NL_NL = 'nl-NL'
PT_BR = 'pt-BR'
ZH_CN = 'zh-CN'
##############################################################################
# Models
##############################################################################
[docs]class CustomModel():
"""
Information about an existing custom model.
:attr str customization_id: The customization ID (GUID) of the custom model. The
**Create a custom model** method returns only this field. It does not not return
the other fields of this object.
:attr str name: (optional) The name of the custom model.
:attr str language: (optional) The language identifier of the custom model (for
example, `en-US`).
:attr str owner: (optional) The GUID of the credentials for the instance of the
service that owns the custom model.
:attr str created: (optional) The date and time in Coordinated Universal Time
(UTC) at which the custom model was created. The value is provided in full ISO
8601 format (`YYYY-MM-DDThh:mm:ss.sTZD`).
:attr str last_modified: (optional) The date and time in Coordinated Universal
Time (UTC) at which the custom model was last modified. The `created` and
`updated` fields are equal when a model is first added but has yet to be
updated. The value is provided in full ISO 8601 format
(`YYYY-MM-DDThh:mm:ss.sTZD`).
:attr str description: (optional) The description of the custom model.
:attr List[Word] words: (optional) An array of `Word` objects that lists the
words and their translations from the custom model. The words are listed in
alphabetical order, with uppercase letters listed before lowercase letters. The
array is empty if no words are defined for the custom model. This field is
returned only by the **Get a custom model** method.
:attr List[Prompt] prompts: (optional) An array of `Prompt` objects that
provides information about the prompts that are defined for the specified custom
model. The array is empty if no prompts are defined for the custom model. This
field is returned only by the **Get a custom model** method.
"""
def __init__(self,
customization_id: str,
*,
name: str = None,
language: str = None,
owner: str = None,
created: str = None,
last_modified: str = None,
description: str = None,
words: List['Word'] = None,
prompts: List['Prompt'] = None) -> None:
"""
Initialize a CustomModel object.
:param str customization_id: The customization ID (GUID) of the custom
model. The **Create a custom model** method returns only this field. It
does not not return the other fields of this object.
:param str name: (optional) The name of the custom model.
:param str language: (optional) The language identifier of the custom model
(for example, `en-US`).
:param str owner: (optional) The GUID of the credentials for the instance
of the service that owns the custom model.
:param str created: (optional) The date and time in Coordinated Universal
Time (UTC) at which the custom model was created. The value is provided in
full ISO 8601 format (`YYYY-MM-DDThh:mm:ss.sTZD`).
:param str last_modified: (optional) The date and time in Coordinated
Universal Time (UTC) at which the custom model was last modified. The
`created` and `updated` fields are equal when a model is first added but
has yet to be updated. The value is provided in full ISO 8601 format
(`YYYY-MM-DDThh:mm:ss.sTZD`).
:param str description: (optional) The description of the custom model.
:param List[Word] words: (optional) An array of `Word` objects that lists
the words and their translations from the custom model. The words are
listed in alphabetical order, with uppercase letters listed before
lowercase letters. The array is empty if no words are defined for the
custom model. This field is returned only by the **Get a custom model**
method.
:param List[Prompt] prompts: (optional) An array of `Prompt` objects that
provides information about the prompts that are defined for the specified
custom model. The array is empty if no prompts are defined for the custom
model. This field is returned only by the **Get a custom model** method.
"""
self.customization_id = customization_id
self.name = name
self.language = language
self.owner = owner
self.created = created
self.last_modified = last_modified
self.description = description
self.words = words
self.prompts = prompts
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'CustomModel':
"""Initialize a CustomModel object from a json dictionary."""
args = {}
if 'customization_id' in _dict:
args['customization_id'] = _dict.get('customization_id')
else:
raise ValueError(
'Required property \'customization_id\' not present in CustomModel JSON'
)
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'language' in _dict:
args['language'] = _dict.get('language')
if 'owner' in _dict:
args['owner'] = _dict.get('owner')
if 'created' in _dict:
args['created'] = _dict.get('created')
if 'last_modified' in _dict:
args['last_modified'] = _dict.get('last_modified')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'words' in _dict:
args['words'] = [Word.from_dict(x) for x in _dict.get('words')]
if 'prompts' in _dict:
args['prompts'] = [
Prompt.from_dict(x) for x in _dict.get('prompts')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a CustomModel object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self,
'customization_id') and self.customization_id is not None:
_dict['customization_id'] = self.customization_id
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'language') and self.language is not None:
_dict['language'] = self.language
if hasattr(self, 'owner') and self.owner is not None:
_dict['owner'] = self.owner
if hasattr(self, 'created') and self.created is not None:
_dict['created'] = self.created
if hasattr(self, 'last_modified') and self.last_modified is not None:
_dict['last_modified'] = self.last_modified
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'words') and self.words is not None:
_dict['words'] = [x.to_dict() for x in self.words]
if hasattr(self, 'prompts') and self.prompts is not None:
_dict['prompts'] = [x.to_dict() for x in self.prompts]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this CustomModel object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'CustomModel') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'CustomModel') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class CustomModels():
"""
Information about existing custom models.
:attr List[CustomModel] customizations: An array of `CustomModel` objects that
provides information about each available custom model. The array is empty if
the requesting credentials own no custom models (if no language is specified) or
own no custom models for the specified language.
"""
def __init__(self, customizations: List['CustomModel']) -> None:
"""
Initialize a CustomModels object.
:param List[CustomModel] customizations: An array of `CustomModel` objects
that provides information about each available custom model. The array is
empty if the requesting credentials own no custom models (if no language is
specified) or own no custom models for the specified language.
"""
self.customizations = customizations
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'CustomModels':
"""Initialize a CustomModels object from a json dictionary."""
args = {}
if 'customizations' in _dict:
args['customizations'] = [
CustomModel.from_dict(x) for x in _dict.get('customizations')
]
else:
raise ValueError(
'Required property \'customizations\' not present in CustomModels JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a CustomModels object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'customizations') and self.customizations is not None:
_dict['customizations'] = [x.to_dict() for x in self.customizations]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this CustomModels object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'CustomModels') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'CustomModels') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Prompt():
"""
Information about a custom prompt.
:attr str prompt: The user-specified text of the prompt.
:attr str prompt_id: The user-specified identifier (name) of the prompt.
:attr str status: The status of the prompt:
* `processing`: The service received the request to add the prompt and is
analyzing the validity of the prompt.
* `available`: The service successfully validated the prompt, which is now ready
for use in a speech synthesis request.
* `failed`: The service's validation of the prompt failed. The status of the
prompt includes an `error` field that describes the reason for the failure.
:attr str error: (optional) If the status of the prompt is `failed`, an error
message that describes the reason for the failure. The field is omitted if no
error occurred.
:attr str speaker_id: (optional) The speaker ID (GUID) of the speaker for which
the prompt was defined. The field is omitted if no speaker ID was specified.
"""
def __init__(self,
prompt: str,
prompt_id: str,
status: str,
*,
error: str = None,
speaker_id: str = None) -> None:
"""
Initialize a Prompt object.
:param str prompt: The user-specified text of the prompt.
:param str prompt_id: The user-specified identifier (name) of the prompt.
:param str status: The status of the prompt:
* `processing`: The service received the request to add the prompt and is
analyzing the validity of the prompt.
* `available`: The service successfully validated the prompt, which is now
ready for use in a speech synthesis request.
* `failed`: The service's validation of the prompt failed. The status of
the prompt includes an `error` field that describes the reason for the
failure.
:param str error: (optional) If the status of the prompt is `failed`, an
error message that describes the reason for the failure. The field is
omitted if no error occurred.
:param str speaker_id: (optional) The speaker ID (GUID) of the speaker for
which the prompt was defined. The field is omitted if no speaker ID was
specified.
"""
self.prompt = prompt
self.prompt_id = prompt_id
self.status = status
self.error = error
self.speaker_id = speaker_id
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Prompt':
"""Initialize a Prompt object from a json dictionary."""
args = {}
if 'prompt' in _dict:
args['prompt'] = _dict.get('prompt')
else:
raise ValueError(
'Required property \'prompt\' not present in Prompt JSON')
if 'prompt_id' in _dict:
args['prompt_id'] = _dict.get('prompt_id')
else:
raise ValueError(
'Required property \'prompt_id\' not present in Prompt JSON')
if 'status' in _dict:
args['status'] = _dict.get('status')
else:
raise ValueError(
'Required property \'status\' not present in Prompt JSON')
if 'error' in _dict:
args['error'] = _dict.get('error')
if 'speaker_id' in _dict:
args['speaker_id'] = _dict.get('speaker_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Prompt object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'prompt') and self.prompt is not None:
_dict['prompt'] = self.prompt
if hasattr(self, 'prompt_id') and self.prompt_id is not None:
_dict['prompt_id'] = self.prompt_id
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status
if hasattr(self, 'error') and self.error is not None:
_dict['error'] = self.error
if hasattr(self, 'speaker_id') and self.speaker_id is not None:
_dict['speaker_id'] = self.speaker_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Prompt object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Prompt') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Prompt') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Prompts():
"""
Information about the custom prompts that are defined for a custom model.
:attr List[Prompt] prompts: An array of `Prompt` objects that provides
information about the prompts that are defined for the specified custom model.
The array is empty if no prompts are defined for the custom model.
"""
def __init__(self, prompts: List['Prompt']) -> None:
"""
Initialize a Prompts object.
:param List[Prompt] prompts: An array of `Prompt` objects that provides
information about the prompts that are defined for the specified custom
model. The array is empty if no prompts are defined for the custom model.
"""
self.prompts = prompts
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Prompts':
"""Initialize a Prompts object from a json dictionary."""
args = {}
if 'prompts' in _dict:
args['prompts'] = [
Prompt.from_dict(x) for x in _dict.get('prompts')
]
else:
raise ValueError(
'Required property \'prompts\' not present in Prompts JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Prompts object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'prompts') and self.prompts is not None:
_dict['prompts'] = [x.to_dict() for x in self.prompts]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Prompts object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Prompts') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Prompts') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Pronunciation():
"""
The pronunciation of the specified text.
:attr str pronunciation: The pronunciation of the specified text in the
requested voice and format. If a custom model is specified, the pronunciation
also reflects that custom model.
"""
def __init__(self, pronunciation: str) -> None:
"""
Initialize a Pronunciation object.
:param str pronunciation: The pronunciation of the specified text in the
requested voice and format. If a custom model is specified, the
pronunciation also reflects that custom model.
"""
self.pronunciation = pronunciation
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Pronunciation':
"""Initialize a Pronunciation object from a json dictionary."""
args = {}
if 'pronunciation' in _dict:
args['pronunciation'] = _dict.get('pronunciation')
else:
raise ValueError(
'Required property \'pronunciation\' not present in Pronunciation JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Pronunciation object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'pronunciation') and self.pronunciation is not None:
_dict['pronunciation'] = self.pronunciation
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Pronunciation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Pronunciation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Pronunciation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Speaker():
"""
Information about a speaker model.
:attr str speaker_id: The speaker ID (GUID) of the speaker.
:attr str name: The user-defined name of the speaker.
"""
def __init__(self, speaker_id: str, name: str) -> None:
"""
Initialize a Speaker object.
:param str speaker_id: The speaker ID (GUID) of the speaker.
:param str name: The user-defined name of the speaker.
"""
self.speaker_id = speaker_id
self.name = name
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Speaker':
"""Initialize a Speaker object from a json dictionary."""
args = {}
if 'speaker_id' in _dict:
args['speaker_id'] = _dict.get('speaker_id')
else:
raise ValueError(
'Required property \'speaker_id\' not present in Speaker JSON')
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError(
'Required property \'name\' not present in Speaker JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Speaker object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'speaker_id') and self.speaker_id is not None:
_dict['speaker_id'] = self.speaker_id
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Speaker object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Speaker') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Speaker') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class SpeakerCustomModel():
"""
A custom models for which the speaker has defined prompts.
:attr str customization_id: The customization ID (GUID) of a custom model for
which the speaker has defined one or more prompts.
:attr List[SpeakerPrompt] prompts: An array of `SpeakerPrompt` objects that
provides information about each prompt that the user has defined for the custom
model.
"""
def __init__(self, customization_id: str,
prompts: List['SpeakerPrompt']) -> None:
"""
Initialize a SpeakerCustomModel object.
:param str customization_id: The customization ID (GUID) of a custom model
for which the speaker has defined one or more prompts.
:param List[SpeakerPrompt] prompts: An array of `SpeakerPrompt` objects
that provides information about each prompt that the user has defined for
the custom model.
"""
self.customization_id = customization_id
self.prompts = prompts
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'SpeakerCustomModel':
"""Initialize a SpeakerCustomModel object from a json dictionary."""
args = {}
if 'customization_id' in _dict:
args['customization_id'] = _dict.get('customization_id')
else:
raise ValueError(
'Required property \'customization_id\' not present in SpeakerCustomModel JSON'
)
if 'prompts' in _dict:
args['prompts'] = [
SpeakerPrompt.from_dict(x) for x in _dict.get('prompts')
]
else:
raise ValueError(
'Required property \'prompts\' not present in SpeakerCustomModel JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SpeakerCustomModel object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self,
'customization_id') and self.customization_id is not None:
_dict['customization_id'] = self.customization_id
if hasattr(self, 'prompts') and self.prompts is not None:
_dict['prompts'] = [x.to_dict() for x in self.prompts]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SpeakerCustomModel object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SpeakerCustomModel') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SpeakerCustomModel') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class SpeakerCustomModels():
"""
Custom models for which the speaker has defined prompts.
:attr List[SpeakerCustomModel] customizations: An array of `SpeakerCustomModel`
objects. Each object provides information about the prompts that are defined for
a specified speaker in the custom models that are owned by a specified service
instance. The array is empty if no prompts are defined for the speaker.
"""
def __init__(self, customizations: List['SpeakerCustomModel']) -> None:
"""
Initialize a SpeakerCustomModels object.
:param List[SpeakerCustomModel] customizations: An array of
`SpeakerCustomModel` objects. Each object provides information about the
prompts that are defined for a specified speaker in the custom models that
are owned by a specified service instance. The array is empty if no prompts
are defined for the speaker.
"""
self.customizations = customizations
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'SpeakerCustomModels':
"""Initialize a SpeakerCustomModels object from a json dictionary."""
args = {}
if 'customizations' in _dict:
args['customizations'] = [
SpeakerCustomModel.from_dict(x)
for x in _dict.get('customizations')
]
else:
raise ValueError(
'Required property \'customizations\' not present in SpeakerCustomModels JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SpeakerCustomModels object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'customizations') and self.customizations is not None:
_dict['customizations'] = [x.to_dict() for x in self.customizations]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SpeakerCustomModels object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SpeakerCustomModels') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SpeakerCustomModels') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class SpeakerModel():
"""
The speaker ID of the speaker model.
:attr str speaker_id: The speaker ID (GUID) of the speaker model.
"""
def __init__(self, speaker_id: str) -> None:
"""
Initialize a SpeakerModel object.
:param str speaker_id: The speaker ID (GUID) of the speaker model.
"""
self.speaker_id = speaker_id
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'SpeakerModel':
"""Initialize a SpeakerModel object from a json dictionary."""
args = {}
if 'speaker_id' in _dict:
args['speaker_id'] = _dict.get('speaker_id')
else:
raise ValueError(
'Required property \'speaker_id\' not present in SpeakerModel JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SpeakerModel object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'speaker_id') and self.speaker_id is not None:
_dict['speaker_id'] = self.speaker_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SpeakerModel object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SpeakerModel') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SpeakerModel') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class SpeakerPrompt():
"""
A prompt that a speaker has defined for a custom model.
:attr str prompt: The user-specified text of the prompt.
:attr str prompt_id: The user-specified identifier (name) of the prompt.
:attr str status: The status of the prompt:
* `processing`: The service received the request to add the prompt and is
analyzing the validity of the prompt.
* `available`: The service successfully validated the prompt, which is now ready
for use in a speech synthesis request.
* `failed`: The service's validation of the prompt failed. The status of the
prompt includes an `error` field that describes the reason for the failure.
:attr str error: (optional) If the status of the prompt is `failed`, an error
message that describes the reason for the failure. The field is omitted if no
error occurred.
"""
def __init__(self,
prompt: str,
prompt_id: str,
status: str,
*,
error: str = None) -> None:
"""
Initialize a SpeakerPrompt object.
:param str prompt: The user-specified text of the prompt.
:param str prompt_id: The user-specified identifier (name) of the prompt.
:param str status: The status of the prompt:
* `processing`: The service received the request to add the prompt and is
analyzing the validity of the prompt.
* `available`: The service successfully validated the prompt, which is now
ready for use in a speech synthesis request.
* `failed`: The service's validation of the prompt failed. The status of
the prompt includes an `error` field that describes the reason for the
failure.
:param str error: (optional) If the status of the prompt is `failed`, an
error message that describes the reason for the failure. The field is
omitted if no error occurred.
"""
self.prompt = prompt
self.prompt_id = prompt_id
self.status = status
self.error = error
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'SpeakerPrompt':
"""Initialize a SpeakerPrompt object from a json dictionary."""
args = {}
if 'prompt' in _dict:
args['prompt'] = _dict.get('prompt')
else:
raise ValueError(
'Required property \'prompt\' not present in SpeakerPrompt JSON'
)
if 'prompt_id' in _dict:
args['prompt_id'] = _dict.get('prompt_id')
else:
raise ValueError(
'Required property \'prompt_id\' not present in SpeakerPrompt JSON'
)
if 'status' in _dict:
args['status'] = _dict.get('status')
else:
raise ValueError(
'Required property \'status\' not present in SpeakerPrompt JSON'
)
if 'error' in _dict:
args['error'] = _dict.get('error')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SpeakerPrompt object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'prompt') and self.prompt is not None:
_dict['prompt'] = self.prompt
if hasattr(self, 'prompt_id') and self.prompt_id is not None:
_dict['prompt_id'] = self.prompt_id
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status
if hasattr(self, 'error') and self.error is not None:
_dict['error'] = self.error
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SpeakerPrompt object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SpeakerPrompt') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SpeakerPrompt') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Speakers():
"""
Information about all speaker models for the service instance.
:attr List[Speaker] speakers: An array of `Speaker` objects that provides
information about the speakers for the service instance. The array is empty if
the service instance has no speakers.
"""
def __init__(self, speakers: List['Speaker']) -> None:
"""
Initialize a Speakers object.
:param List[Speaker] speakers: An array of `Speaker` objects that provides
information about the speakers for the service instance. The array is empty
if the service instance has no speakers.
"""
self.speakers = speakers
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Speakers':
"""Initialize a Speakers object from a json dictionary."""
args = {}
if 'speakers' in _dict:
args['speakers'] = [
Speaker.from_dict(x) for x in _dict.get('speakers')
]
else:
raise ValueError(
'Required property \'speakers\' not present in Speakers JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Speakers object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'speakers') and self.speakers is not None:
_dict['speakers'] = [x.to_dict() for x in self.speakers]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Speakers object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Speakers') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Speakers') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class SupportedFeatures():
"""
Additional service features that are supported with the voice.
:attr bool custom_pronunciation: If `true`, the voice can be customized; if
`false`, the voice cannot be customized. (Same as `customizable`.).
:attr bool voice_transformation: If `true`, the voice can be transformed by
using the SSML <voice-transformation> element; if `false`, the voice
cannot be transformed. The feature was available only for the now-deprecated
standard voices. You cannot use the feature with neural voices.
"""
def __init__(self, custom_pronunciation: bool,
voice_transformation: bool) -> None:
"""
Initialize a SupportedFeatures object.
:param bool custom_pronunciation: If `true`, the voice can be customized;
if `false`, the voice cannot be customized. (Same as `customizable`.).
:param bool voice_transformation: If `true`, the voice can be transformed
by using the SSML <voice-transformation> element; if `false`, the
voice cannot be transformed. The feature was available only for the
now-deprecated standard voices. You cannot use the feature with neural
voices.
"""
self.custom_pronunciation = custom_pronunciation
self.voice_transformation = voice_transformation
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'SupportedFeatures':
"""Initialize a SupportedFeatures object from a json dictionary."""
args = {}
if 'custom_pronunciation' in _dict:
args['custom_pronunciation'] = _dict.get('custom_pronunciation')
else:
raise ValueError(
'Required property \'custom_pronunciation\' not present in SupportedFeatures JSON'
)
if 'voice_transformation' in _dict:
args['voice_transformation'] = _dict.get('voice_transformation')
else:
raise ValueError(
'Required property \'voice_transformation\' not present in SupportedFeatures JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SupportedFeatures object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'custom_pronunciation'
) and self.custom_pronunciation is not None:
_dict['custom_pronunciation'] = self.custom_pronunciation
if hasattr(self, 'voice_transformation'
) and self.voice_transformation is not None:
_dict['voice_transformation'] = self.voice_transformation
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SupportedFeatures object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SupportedFeatures') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SupportedFeatures') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Translation():
"""
Information about the translation for the specified text.
:attr str translation: The phonetic or sounds-like translation for the word. A
phonetic translation is based on the SSML format for representing the phonetic
string of a word either as an IPA translation or as an IBM SPR translation. The
Arabic, Chinese, Dutch, Australian English, and Korean languages support only
IPA. A sounds-like is one or more words that, when combined, sound like the
word.
:attr str part_of_speech: (optional) **Japanese only.** The part of speech for
the word. The service uses the value to produce the correct intonation for the
word. You can create only a single entry, with or without a single part of
speech, for any word; you cannot create multiple entries with different parts of
speech for the same word. For more information, see [Working with Japanese
entries](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-rules#jaNotes).
"""
def __init__(self, translation: str, *, part_of_speech: str = None) -> None:
"""
Initialize a Translation object.
:param str translation: The phonetic or sounds-like translation for the
word. A phonetic translation is based on the SSML format for representing
the phonetic string of a word either as an IPA translation or as an IBM SPR
translation. The Arabic, Chinese, Dutch, Australian English, and Korean
languages support only IPA. A sounds-like is one or more words that, when
combined, sound like the word.
:param str part_of_speech: (optional) **Japanese only.** The part of speech
for the word. The service uses the value to produce the correct intonation
for the word. You can create only a single entry, with or without a single
part of speech, for any word; you cannot create multiple entries with
different parts of speech for the same word. For more information, see
[Working with Japanese
entries](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-rules#jaNotes).
"""
self.translation = translation
self.part_of_speech = part_of_speech
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Translation':
"""Initialize a Translation object from a json dictionary."""
args = {}
if 'translation' in _dict:
args['translation'] = _dict.get('translation')
else:
raise ValueError(
'Required property \'translation\' not present in Translation JSON'
)
if 'part_of_speech' in _dict:
args['part_of_speech'] = _dict.get('part_of_speech')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Translation object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'translation') and self.translation is not None:
_dict['translation'] = self.translation
if hasattr(self, 'part_of_speech') and self.part_of_speech is not None:
_dict['part_of_speech'] = self.part_of_speech
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Translation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Translation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Translation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class PartOfSpeechEnum(str, Enum):
"""
**Japanese only.** The part of speech for the word. The service uses the value to
produce the correct intonation for the word. You can create only a single entry,
with or without a single part of speech, for any word; you cannot create multiple
entries with different parts of speech for the same word. For more information,
see [Working with Japanese
entries](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-rules#jaNotes).
"""
DOSI = 'Dosi'
FUKU = 'Fuku'
GOBI = 'Gobi'
HOKA = 'Hoka'
JODO = 'Jodo'
JOSI = 'Josi'
KATO = 'Kato'
KEDO = 'Kedo'
KEYO = 'Keyo'
KIGO = 'Kigo'
KOYU = 'Koyu'
MESI = 'Mesi'
RETA = 'Reta'
STBI = 'Stbi'
STTO = 'Stto'
STZO = 'Stzo'
SUJI = 'Suji'
[docs]class Voice():
"""
Information about an available voice.
:attr str url: The URI of the voice.
:attr str gender: The gender of the voice: `male` or `female`.
:attr str name: The name of the voice. Use this as the voice identifier in all
requests.
:attr str language: The language and region of the voice (for example, `en-US`).
:attr str description: A textual description of the voice.
:attr bool customizable: If `true`, the voice can be customized; if `false`, the
voice cannot be customized. (Same as `custom_pronunciation`; maintained for
backward compatibility.).
:attr SupportedFeatures supported_features: Additional service features that are
supported with the voice.
:attr CustomModel customization: (optional) Returns information about a
specified custom model. This field is returned only by the **Get a voice**
method and only when you specify the customization ID of a custom model.
"""
def __init__(self,
url: str,
gender: str,
name: str,
language: str,
description: str,
customizable: bool,
supported_features: 'SupportedFeatures',
*,
customization: 'CustomModel' = None) -> None:
"""
Initialize a Voice object.
:param str url: The URI of the voice.
:param str gender: The gender of the voice: `male` or `female`.
:param str name: The name of the voice. Use this as the voice identifier in
all requests.
:param str language: The language and region of the voice (for example,
`en-US`).
:param str description: A textual description of the voice.
:param bool customizable: If `true`, the voice can be customized; if
`false`, the voice cannot be customized. (Same as `custom_pronunciation`;
maintained for backward compatibility.).
:param SupportedFeatures supported_features: Additional service features
that are supported with the voice.
:param CustomModel customization: (optional) Returns information about a
specified custom model. This field is returned only by the **Get a voice**
method and only when you specify the customization ID of a custom model.
"""
self.url = url
self.gender = gender
self.name = name
self.language = language
self.description = description
self.customizable = customizable
self.supported_features = supported_features
self.customization = customization
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Voice':
"""Initialize a Voice object from a json dictionary."""
args = {}
if 'url' in _dict:
args['url'] = _dict.get('url')
else:
raise ValueError(
'Required property \'url\' not present in Voice JSON')
if 'gender' in _dict:
args['gender'] = _dict.get('gender')
else:
raise ValueError(
'Required property \'gender\' not present in Voice JSON')
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError(
'Required property \'name\' not present in Voice JSON')
if 'language' in _dict:
args['language'] = _dict.get('language')
else:
raise ValueError(
'Required property \'language\' not present in Voice JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
else:
raise ValueError(
'Required property \'description\' not present in Voice JSON')
if 'customizable' in _dict:
args['customizable'] = _dict.get('customizable')
else:
raise ValueError(
'Required property \'customizable\' not present in Voice JSON')
if 'supported_features' in _dict:
args['supported_features'] = SupportedFeatures.from_dict(
_dict.get('supported_features'))
else:
raise ValueError(
'Required property \'supported_features\' not present in Voice JSON'
)
if 'customization' in _dict:
args['customization'] = CustomModel.from_dict(
_dict.get('customization'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Voice object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'gender') and self.gender is not None:
_dict['gender'] = self.gender
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'language') and self.language is not None:
_dict['language'] = self.language
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'customizable') and self.customizable is not None:
_dict['customizable'] = self.customizable
if hasattr(
self,
'supported_features') and self.supported_features is not None:
_dict['supported_features'] = self.supported_features.to_dict()
if hasattr(self, 'customization') and self.customization is not None:
_dict['customization'] = self.customization.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Voice object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Voice') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Voice') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Voices():
"""
Information about all available voices.
:attr List[Voice] voices: A list of available voices.
"""
def __init__(self, voices: List['Voice']) -> None:
"""
Initialize a Voices object.
:param List[Voice] voices: A list of available voices.
"""
self.voices = voices
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Voices':
"""Initialize a Voices object from a json dictionary."""
args = {}
if 'voices' in _dict:
args['voices'] = [Voice.from_dict(x) for x in _dict.get('voices')]
else:
raise ValueError(
'Required property \'voices\' not present in Voices JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Voices object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'voices') and self.voices is not None:
_dict['voices'] = [x.to_dict() for x in self.voices]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Voices object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Voices') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Voices') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Word():
"""
Information about a word for the custom model.
:attr str word: The word for the custom model. The maximum length of a word is
49 characters.
:attr str translation: The phonetic or sounds-like translation for the word. A
phonetic translation is based on the SSML format for representing the phonetic
string of a word either as an IPA or IBM SPR translation. The Arabic, Chinese,
Dutch, Australian English, and Korean languages support only IPA. A sounds-like
translation consists of one or more words that, when combined, sound like the
word. The maximum length of a translation is 499 characters.
:attr str part_of_speech: (optional) **Japanese only.** The part of speech for
the word. The service uses the value to produce the correct intonation for the
word. You can create only a single entry, with or without a single part of
speech, for any word; you cannot create multiple entries with different parts of
speech for the same word. For more information, see [Working with Japanese
entries](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-rules#jaNotes).
"""
def __init__(self,
word: str,
translation: str,
*,
part_of_speech: str = None) -> None:
"""
Initialize a Word object.
:param str word: The word for the custom model. The maximum length of a
word is 49 characters.
:param str translation: The phonetic or sounds-like translation for the
word. A phonetic translation is based on the SSML format for representing
the phonetic string of a word either as an IPA or IBM SPR translation. The
Arabic, Chinese, Dutch, Australian English, and Korean languages support
only IPA. A sounds-like translation consists of one or more words that,
when combined, sound like the word. The maximum length of a translation is
499 characters.
:param str part_of_speech: (optional) **Japanese only.** The part of speech
for the word. The service uses the value to produce the correct intonation
for the word. You can create only a single entry, with or without a single
part of speech, for any word; you cannot create multiple entries with
different parts of speech for the same word. For more information, see
[Working with Japanese
entries](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-rules#jaNotes).
"""
self.word = word
self.translation = translation
self.part_of_speech = part_of_speech
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Word':
"""Initialize a Word object from a json dictionary."""
args = {}
if 'word' in _dict:
args['word'] = _dict.get('word')
else:
raise ValueError(
'Required property \'word\' not present in Word JSON')
if 'translation' in _dict:
args['translation'] = _dict.get('translation')
else:
raise ValueError(
'Required property \'translation\' not present in Word JSON')
if 'part_of_speech' in _dict:
args['part_of_speech'] = _dict.get('part_of_speech')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Word object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'word') and self.word is not None:
_dict['word'] = self.word
if hasattr(self, 'translation') and self.translation is not None:
_dict['translation'] = self.translation
if hasattr(self, 'part_of_speech') and self.part_of_speech is not None:
_dict['part_of_speech'] = self.part_of_speech
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Word object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Word') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Word') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class PartOfSpeechEnum(str, Enum):
"""
**Japanese only.** The part of speech for the word. The service uses the value to
produce the correct intonation for the word. You can create only a single entry,
with or without a single part of speech, for any word; you cannot create multiple
entries with different parts of speech for the same word. For more information,
see [Working with Japanese
entries](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-rules#jaNotes).
"""
DOSI = 'Dosi'
FUKU = 'Fuku'
GOBI = 'Gobi'
HOKA = 'Hoka'
JODO = 'Jodo'
JOSI = 'Josi'
KATO = 'Kato'
KEDO = 'Kedo'
KEYO = 'Keyo'
KIGO = 'Kigo'
KOYU = 'Koyu'
MESI = 'Mesi'
RETA = 'Reta'
STBI = 'Stbi'
STTO = 'Stto'
STZO = 'Stzo'
SUJI = 'Suji'
[docs]class Words():
"""
For the **Add custom words** method, one or more words that are to be added or updated
for the custom model and the translation for each specified word.
For the **List custom words** method, the words and their translations from the custom
model.
:attr List[Word] words: The **Add custom words** method accepts an array of
`Word` objects. Each object provides a word that is to be added or updated for
the custom model and the word's translation.
The **List custom words** method returns an array of `Word` objects. Each object
shows a word and its translation from the custom model. The words are listed in
alphabetical order, with uppercase letters listed before lowercase letters. The
array is empty if the custom model contains no words.
"""
def __init__(self, words: List['Word']) -> None:
"""
Initialize a Words object.
:param List[Word] words: The **Add custom words** method accepts an array
of `Word` objects. Each object provides a word that is to be added or
updated for the custom model and the word's translation.
The **List custom words** method returns an array of `Word` objects. Each
object shows a word and its translation from the custom model. The words
are listed in alphabetical order, with uppercase letters listed before
lowercase letters. The array is empty if the custom model contains no
words.
"""
self.words = words
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Words':
"""Initialize a Words object from a json dictionary."""
args = {}
if 'words' in _dict:
args['words'] = [Word.from_dict(x) for x in _dict.get('words')]
else:
raise ValueError(
'Required property \'words\' not present in Words JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Words object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'words') and self.words is not None:
_dict['words'] = [x.to_dict() for x in self.words]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Words object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Words') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Words') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other