watson_developer_cloud.speech_to_text_v1 module

The IBM® Speech to Text service provides an API that uses IBM’s speech-recognition capabilities to produce transcripts of spoken audio. The service can transcribe speech from various languages and audio formats. It addition to basic transcription, the service can produce detailed information about many aspects of the audio. For most languages, the service supports two sampling rates, broadband and narrowband. It returns all JSON response content in the UTF-8 character set. For more information about the service, see the [IBM® Cloud documentation](https://console.bluemix.net/docs/services/speech-to-text/index.html). ### API usage guidelines * Audio formats: The service accepts audio in many formats (MIME types). See [Audio formats](https://console.bluemix.net/docs/services/speech-to-text/audio-formats.html). * HTTP interfaces: The service provides three HTTP interfaces for speech recognition. The sessionless interface includes a single synchronous method. The session-based interface includes multiple synchronous methods for maintaining a long, multi-turn exchange with the service. And the asynchronous interface provides multiple methods that use registered callbacks and polling for non-blocking recognition. See [The HTTP REST interface](https://console.bluemix.net/docs/services/speech-to-text/http.html) and [The asynchronous HTTP interface](https://console.bluemix.net/docs/services/speech-to-text/async.html). * WebSocket interface: The service also offers a WebSocket interface for speech recognition. The WebSocket interface provides a full-duplex, low-latency communication channel. Clients send requests and audio to the service and receive results over a single connection in an asynchronous fashion. See [The WebSocket interface](https://console.bluemix.net/docs/services/speech-to-text/websockets.html). * Customization: Use language model customization to expand the vocabulary of a base model with domain-specific terminology. Use acoustic model customization to adapt a base model for the acoustic characteristics of your audio. Language model customization is generally available for production use by most supported languages; acoustic model customization is beta functionality that is available for all supported languages. See [The customization interface](https://console.bluemix.net/docs/services/speech-to-text/custom.html). * Customization IDs: Many methods accept a customization ID to identify a custom language or custom acoustic model. Customization IDs are Globally Unique Identifiers (GUIDs). They are hexadecimal strings that have the format xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx. * `X-Watson-Learning-Opt-Out`: By default, all Watson services log requests and their results. Logging is done only to improve the services for future users. The logged data is not shared or made public. To prevent IBM from accessing your data for general service improvements, set the X-Watson-Learning-Opt-Out request header to true for all requests. You must set the header on each request that you do not want IBM to access for general service improvements.

Methods of the customization interface do not log corpora, words, and audio resources

that you use to build custom models. Your training data is never used to improve the service’s base models. However, the service does log such data when a custom model is used with a recognition request. You must set the X-Watson-Learning-Opt-Out request header to true to prevent IBM from accessing the data to improve the service. * `X-Watson-Metadata`: This header allows you to associate a customer ID with data that is passed with a request. If necessary, you can use the Delete labeled data method to delete the data for a customer ID. See [Information security](https://console.bluemix.net/docs/services/speech-to-text/information-security.html).

class SpeechToTextV1(url='https://stream.watsonplatform.net/speech-to-text/api', username=None, password=None, iam_api_key=None, iam_access_token=None, iam_url=None)

Bases: watson_developer_cloud.watson_service.WatsonService

The Speech to Text V1 service.

default_url = 'https://stream.watsonplatform.net/speech-to-text/api'

get_model(model_id, **kwargs)

Get a model.

Gets information for a single specified language model that is available for use with the service. The information includes the name of the model and its minimum sampling rate in Hertz, among other things.

Parameters:model_id (str) – The identifier of the model in the form of its name from the

output of the Get models method. :param dict headers: A dict containing the request headers :return: A dict containing the SpeechModel response. :rtype: dict

list_models(**kwargs)

List models.

Lists all language models that are available for use with the service. The information includes the name of the model and its minimum sampling rate in Hertz, among other things.

Parameters:headers (dict) – A dict containing the request headers Returns:A dict containing the SpeechModels response. Return type:dict

models(**kwargs)

recognize(model=None, customization_id=None, acoustic_customization_id=None, customization_weight=None, version=None, audio=None, content_type=None, inactivity_timeout=None, keywords=None, keywords_threshold=None, max_alternatives=None, word_alternatives_threshold=None, word_confidence=None, timestamps=None, profanity_filter=None, smart_formatting=None, speaker_labels=None, **kwargs)

Recognize audio (sessionless).

Sends audio and returns transcription results for a sessionless recognition request. Returns only the final results; to enable interim results, use session-based requests or the WebSocket API. The service imposes a data size limit of 100 MB. It automatically detects the endianness of the incoming audio and, for audio that includes multiple channels, downmixes the audio to one-channel mono during transcoding. (For the audio/l16 format, you can specify the endianness.) ### Streaming mode

For requests to transcribe live audio as it becomes available, you must set the

Transfer-Encoding header to chunked to use streaming mode. In streaming mode, the server closes the connection (status code 408) if the service receives no data chunk for 30 seconds and the service has no audio to transcribe for 30 seconds. The server also closes the connection (status code 400) if no speech is detected for inactivity_timeout seconds of audio (not processing time); use the inactivity_timeout parameter to change the default of 30 seconds. ### Audio formats (content types)

Use the Content-Type header to specify the audio format (MIME type) of the

audio. The service accepts the following formats: * audio/basic (Use only with narrowband models.) * audio/flac * audio/l16 (Specify the sampling rate (rate) and optionally the number of channels (channels) and endianness (endianness) of the audio.) * audio/mp3 * audio/mpeg * audio/mulaw (Specify the sampling rate (rate) of the audio.) * audio/ogg (The service automatically detects the codec of the input audio.) * audio/ogg;codecs=opus * audio/ogg;codecs=vorbis * audio/wav (Provide audio with a maximum of nine channels.) * audio/webm (The service automatically detects the codec of the input audio.) * audio/webm;codecs=opus * audio/webm;codecs=vorbis For information about the supported audio formats, including specifying the sampling rate, channels, and endianness for the indicated formats, see [Audio formats](https://console.bluemix.net/docs/services/speech-to-text/audio-formats.html). ### Multipart speech recognition

The method also supports multipart recognition requests. With multipart requests,

you pass all audio data as multipart form data. You specify some parameters as request headers and query parameters, but you pass JSON metadata as form data to control most aspects of the transcription. The multipart approach is intended for use with browsers for which JavaScript is disabled or when the parameters used with the request are greater than the 8 KB limit imposed by most HTTP servers and proxies. You can encounter this limit, for example, if you want to spot a very large number of keywords. For information about submitting a multipart request, see [Submitting multipart requests as form data](https://console.bluemix.net/docs/services/speech-to-text/http.html#HTTP-multi).

Parameters:model (str) – The identifier of the model that is to be used for the

recognition request or, for the Create a session method, with the new session. :param str customization_id: The customization ID (GUID) of a custom language model that is to be used with the recognition request or, for the Create a session method, with the new session. The base model of the specified custom language model must match the model specified with the model parameter. You must make the request with service credentials created for the instance of the service that owns the custom model. By default, no custom language model is used. :param str acoustic_customization_id: The customization ID (GUID) of a custom acoustic model that is to be used with the recognition request or, for the Create a session method, with the new session. The base model of the specified custom acoustic model must match the model specified with the model parameter. You must make the request with service credentials created for the instance of the service that owns the custom model. By default, no custom acoustic model is used. :param float customization_weight: If you specify the customization ID (GUID) of a custom language model with the recognition request or, for sessions, with the Create a session method, the customization weight tells the service how much weight to give to words from the custom language model compared to those from the base model for the current request. Specify a value between 0.0 and 1.0. Unless a different customization weight was specified for the custom model when it was trained, the default value is 0.3. A customization weight that you specify overrides a weight that was specified when the custom model was trained. The default value yields the best performance in general. Assign a higher value if your audio makes frequent use of OOV words from the custom model. Use caution when setting the weight: a higher value can improve the accuracy of phrases from the custom model’s domain, but it can negatively affect performance on non-domain phrases. :param str version: The version of the specified base model that is to be used with recognition request or, for the Create a session method, with the new session. Multiple versions of a base model can exist when a model is updated for internal improvements. The parameter is intended primarily for use with custom models that have been upgraded for a new base model. The default value depends on whether the parameter is used with or without a custom model. For more information, see [Base model version](https://console.bluemix.net/docs/services/speech-to-text/input.html#version). :param str audio: The audio to transcribe in the format specified by the Content-Type header. :param str content_type: The type of the input: audio/basic, audio/flac, audio/l16, audio/mp3, audio/mpeg, audio/mulaw, audio/ogg, audio/ogg;codecs=opus, audio/ogg;codecs=vorbis, audio/wav, audio/webm, audio/webm;codecs=opus, or audio/webm;codecs=vorbis. :param int inactivity_timeout: The time in seconds after which, if only silence (no speech) is detected in submitted audio, the connection is closed with a 400 error. Useful for stopping audio submission from a live microphone when a user simply walks away. Use -1 for infinity. :param list[str] keywords: An array of keyword strings to spot in the audio. Each keyword string can include one or more tokens. Keywords are spotted only in the final hypothesis, not in interim results. If you specify any keywords, you must also specify a keywords threshold. You can spot a maximum of 1000 keywords. Omit the parameter or specify an empty array if you do not need to spot keywords. :param float keywords_threshold: A confidence value that is the lower bound for spotting a keyword. A word is considered to match a keyword if its confidence is greater than or equal to the threshold. Specify a probability between 0 and 1 inclusive. No keyword spotting is performed if you omit the parameter. If you specify a threshold, you must also specify one or more keywords. :param int max_alternatives: The maximum number of alternative transcripts to be returned. By default, a single transcription is returned. :param float word_alternatives_threshold: A confidence value that is the lower bound for identifying a hypothesis as a possible word alternative (also known as “Confusion Networks”). An alternative word is considered if its confidence is greater than or equal to the threshold. Specify a probability between 0 and 1 inclusive. No alternative words are computed if you omit the parameter. :param bool word_confidence: If true, a confidence measure in the range of 0 to 1 is returned for each word. By default, no word confidence measures are returned. :param bool timestamps: If true, time alignment is returned for each word. By default, no timestamps are returned. :param bool profanity_filter: If true (the default), filters profanity from all output except for keyword results by replacing inappropriate words with a series of asterisks. Set the parameter to false to return results with no censoring. Applies to US English transcription only. :param bool smart_formatting: If true, converts dates, times, series of digits and numbers, phone numbers, currency values, and internet addresses into more readable, conventional representations in the final transcript of a recognition request. For US English, also converts certain keyword strings to punctuation symbols. By default, no smart formatting is performed. Applies to US English and Spanish transcription only. :param bool speaker_labels: If true, the response includes labels that identify which words were spoken by which participants in a multi-person exchange. By default, no speaker labels are returned. Setting speaker_labels to true forces the timestamps parameter to be true, regardless of whether you specify false for the parameter.

To determine whether a language model supports speaker labels, use the **Get

models** method and check that the attribute speaker_labels is set to true. You can also refer to [Speaker labels](https://console.bluemix.net/docs/services/speech-to-text/output.html#speaker_labels). :param dict headers: A dict containing the request headers :return: A dict containing the SpeechRecognitionResults response. :rtype: dict

recognize_with_websocket(audio=None, content_type='audio/l16; rate=44100', model='en-US_BroadbandModel', recognize_callback=None, customization_id=None, acoustic_customization_id=None, customization_weight=None, version=None, inactivity_timeout=None, interim_results=True, keywords=None, keywords_threshold=None, max_alternatives=1, word_alternatives_threshold=None, word_confidence=False, timestamps=False, profanity_filter=None, smart_formatting=False, speaker_labels=None, **kwargs)

Sends audio for speech recognition using web sockets.

Parameters:model (str) – The identifier of the model that is to be used for the

recognition request or, for the Create a session method, with the new session. :param str customization_id: The customization ID (GUID) of a custom language model that is to be used with the recognition request or, for the Create a session method, with the new session. The base model of the specified custom language model must match the model specified with the model parameter. You must make the request with service credentials created for the instance of the service that owns the custom model. By default, no custom language model is used. :param str acoustic_customization_id: The customization ID (GUID) of a custom acoustic model that is to be used with the recognition request or, for the Create a session method, with the new session. The base model of the specified custom acoustic model must match the model specified with the model parameter. You must make the request with service credentials created for the instance of the service that owns the custom model. By default, no custom acoustic model is used. :param float customization_weight: If you specify the customization ID (GUID) of a custom language model with the recognition request or, for sessions, with the Create a session method, the customization weight tells the service how much weight to give to words from the custom language model compared to those from the base model for the current request. Specify a value between 0.0 and 1.0. Unless a different customization weight was specified for the custom model when it was trained, the default value is 0.3. A customization weight that you specify overrides a weight that was specified when the custom model was trained. The default value yields the best performance in general. Assign a higher value if your audio makes frequent use of OOV words from the custom model. Use caution when setting the weight: a higher value can improve the accuracy of phrases from the custom model’s domain, but it can negatively affect performance on non-domain phrases. :param str version: The version of the specified base model that is to be used with recognition request or, for the Create a session method, with the new session. Multiple versions of a base model can exist when a model is updated for internal improvements. The parameter is intended primarily for use with custom models that have been upgraded for a new base model. The default value depends on whether the parameter is used with or without a custom model. For more information, see [Base model version](https://console.bluemix.net/docs/services/speech-to-text/input.html#version). :param str audio: The audio to transcribe in the format specified by the Content-Type header. :param str content_type: The type of the input: audio/basic, audio/flac, audio/l16, audio/mp3, audio/mpeg, audio/mulaw, audio/ogg, audio/ogg;codecs=opus, audio/ogg;codecs=vorbis, audio/wav, audio/webm, audio/webm;codecs=opus, or audio/webm;codecs=vorbis. :param int inactivity_timeout: The time in seconds after which, if only silence (no speech) is detected in submitted audio, the connection is closed with a 400 error. Useful for stopping audio submission from a live microphone when a user simply walks away. Use -1 for infinity. :param list[str] keywords: An array of keyword strings to spot in the audio. Each keyword string can include one or more tokens. Keywords are spotted only in the final hypothesis, not in interim results. If you specify any keywords, you must also specify a keywords threshold. You can spot a maximum of 1000 keywords. Omit the parameter or specify an empty array if you do not need to spot keywords. :param float keywords_threshold: A confidence value that is the lower bound for spotting a keyword. A word is considered to match a keyword if its confidence is greater than or equal to the threshold. Specify a probability between 0 and 1 inclusive. No keyword spotting is performed if you omit the parameter. If you specify a threshold, you must also specify one or more keywords. :param int max_alternatives: The maximum number of alternative transcripts to be returned. By default, a single transcription is returned. :param float word_alternatives_threshold: A confidence value that is the lower bound for identifying a hypothesis as a possible word alternative (also known as “Confusion Networks”). An alternative word is considered if its confidence is greater than or equal to the threshold. Specify a probability between 0 and 1 inclusive. No alternative words are computed if you omit the parameter. :param bool word_confidence: If true, a confidence measure in the range of 0 to 1 is returned for each word. By default, no word confidence measures are returned. :param bool timestamps: If true, time alignment is returned for each word. By default, no timestamps are returned. :param bool profanity_filter: If true (the default), filters profanity from all output except for keyword results by replacing inappropriate words with a series of asterisks. Set the parameter to false to return results with no censoring. Applies to US English transcription only. :param bool smart_formatting: If true, converts dates, times, series of digits and numbers, phone numbers, currency values, and internet addresses into more readable, conventional representations in the final transcript of a recognition request. For US English, also converts certain keyword strings to punctuation symbols. By default, no smart formatting is performed. Applies to US English and Spanish transcription only. :param bool speaker_labels: If true, the response includes labels that identify which words were spoken by which participants in a multi-person exchange. By default, no speaker labels are returned. Setting speaker_labels to true forces the timestamps parameter to be true, regardless of whether you specify false for the parameter.

To determine whether a language model supports speaker labels, use the **Get

models** method and check that the attribute speaker_labels is set to true. You can also refer to [Speaker labels](https://console.bluemix.net/docs/services/speech-to-text/output.html#speaker_labels). :param dict headers: A dict containing the request headers :return: A dict containing the SpeechRecognitionResults response. :rtype: dict

check_job(id, **kwargs)

Check a job.

Returns information about the specified job. The response always includes the status of the job and its creation and update times. If the status is completed, the response includes the results of the recognition request. You must submit the request with the service credentials of the user who created the job. You can use the method to retrieve the results of any job, regardless of whether it was submitted with a callback URL and the recognitions.completed_with_results event, and you can retrieve the results multiple times for as long as they remain available. Use the Check jobs method to request information about the most recent jobs associated with the calling user.

Parameters:

• id (str) – The ID of the asynchronous job.
• headers (dict) – A dict containing the request headers

Returns:

A dict containing the RecognitionJob response.

Return type:

dict

check_jobs(**kwargs)

Check jobs.

Returns the ID and status of the latest 100 outstanding jobs associated with the service credentials with which it is called. The method also returns the creation and update times of each job, and, if a job was created with a callback URL and a user token, the user token for the job. To obtain the results for a job whose status is completed or not one of the latest 100 outstanding jobs, use the Check a job method. A job and its results remain available until you delete them with the Delete a job method or until the job’s time to live expires, whichever comes first.

Parameters:headers (dict) – A dict containing the request headers Returns:A dict containing the RecognitionJobs response. Return type:dict

create_job(audio, content_type, model=None, callback_url=None, events=None, user_token=None, results_ttl=None, customization_id=None, acoustic_customization_id=None, customization_weight=None, version=None, inactivity_timeout=None, keywords=None, keywords_threshold=None, max_alternatives=None, word_alternatives_threshold=None, word_confidence=None, timestamps=None, profanity_filter=None, smart_formatting=None, speaker_labels=None, **kwargs)

Create a job.

Creates a job for a new asynchronous recognition request. The job is owned by the user whose service credentials are used to create it. How you learn the status and results of a job depends on the parameters you include with the job creation request: * By callback notification: Include the callback_url parameter to specify a URL to which the service is to send callback notifications when the status of the job changes. Optionally, you can also include the events and user_token parameters to subscribe to specific events and to specify a string that is to be included with each notification for the job. * By polling the service: Omit the callback_url, events, and user_token parameters. You must then use the Check jobs or Check a job methods to check the status of the job, using the latter to retrieve the results when the job is complete. The two approaches are not mutually exclusive. You can poll the service for job status or obtain results from the service manually even if you include a callback URL. In both cases, you can include the results_ttl parameter to specify how long the results are to remain available after the job is complete. For detailed usage information about the two approaches, including callback notifications, see [Creating a job](https://console.bluemix.net/docs/services/speech-to-text/async.html#create). Using the HTTPS Check a job method to retrieve results is more secure than receiving them via callback notification over HTTP because it provides confidentiality in addition to authentication and data integrity. The method supports the same basic parameters as other HTTP and WebSocket recognition requests. The service imposes a data size limit of 100 MB. It automatically detects the endianness of the incoming audio and, for audio that includes multiple channels, downmixes the audio to one-channel mono during transcoding. (For the audio/l16 format, you can specify the endianness.) ### Audio formats (content types)

Use the Content-Type parameter to specify the audio format (MIME type) of the

audio: * audio/basic (Use only with narrowband models.) * audio/flac * audio/l16 (Specify the sampling rate (rate) and optionally the number of channels (channels) and endianness (endianness) of the audio.) * audio/mp3 * audio/mpeg * audio/mulaw (Specify the sampling rate (rate) of the audio.) * audio/ogg (The service automatically detects the codec of the input audio.) * audio/ogg;codecs=opus * audio/ogg;codecs=vorbis * audio/wav (Provide audio with a maximum of nine channels.) * audio/webm (The service automatically detects the codec of the input audio.) * audio/webm;codecs=opus * audio/webm;codecs=vorbis For information about the supported audio formats, including specifying the sampling rate, channels, and endianness for the indicated formats, see [Audio formats](https://console.bluemix.net/docs/services/speech-to-text/audio-formats.html).

Parameters:audio (str) – The audio to transcribe in the format specified by the

Content-Type header. :param str content_type: The type of the input: audio/basic, audio/flac, audio/l16, audio/mp3, audio/mpeg, audio/mulaw, audio/ogg, audio/ogg;codecs=opus, audio/ogg;codecs=vorbis, audio/wav, audio/webm, audio/webm;codecs=opus, or audio/webm;codecs=vorbis. :param str model: The identifier of the model that is to be used for the recognition request or, for the Create a session method, with the new session. :param str callback_url: A URL to which callback notifications are to be sent. The URL must already be successfully white-listed by using the Register a callback method. Omit the parameter to poll the service for job completion and results. You can include the same callback URL with any number of job creation requests. Use the user_token parameter to specify a unique user-specified string with each job to differentiate the callback notifications for the jobs. :param str events: If the job includes a callback URL, a comma-separated list of notification events to which to subscribe. Valid events are: recognitions.started generates a callback notification when the service begins to process the job. recognitions.completed generates a callback notification when the job is complete; you must use the Check a job method to retrieve the results before they time out or are deleted. recognitions.completed_with_results generates a callback notification when the job is complete; the notification includes the results of the request. recognitions.failed generates a callback notification if the service experiences an error while processing the job. Omit the parameter to subscribe to the default events: recognitions.started, recognitions.completed, and recognitions.failed. The recognitions.completed and recognitions.completed_with_results events are incompatible; you can specify only of the two events. If the job does not include a callback URL, omit the parameter. :param str user_token: If the job includes a callback URL, a user-specified string that the service is to include with each callback notification for the job; the token allows the user to maintain an internal mapping between jobs and notification events. If the job does not include a callback URL, omit the parameter. :param int results_ttl: The number of minutes for which the results are to be available after the job has finished. If not delivered via a callback, the results must be retrieved within this time. Omit the parameter to use a time to live of one week. The parameter is valid with or without a callback URL. :param str customization_id: The customization ID (GUID) of a custom language model that is to be used with the recognition request or, for the Create a session method, with the new session. The base model of the specified custom language model must match the model specified with the model parameter. You must make the request with service credentials created for the instance of the service that owns the custom model. By default, no custom language model is used. :param str acoustic_customization_id: The customization ID (GUID) of a custom acoustic model that is to be used with the recognition request or, for the Create a session method, with the new session. The base model of the specified custom acoustic model must match the model specified with the model parameter. You must make the request with service credentials created for the instance of the service that owns the custom model. By default, no custom acoustic model is used. :param float customization_weight: If you specify the customization ID (GUID) of a custom language model with the recognition request or, for sessions, with the Create a session method, the customization weight tells the service how much weight to give to words from the custom language model compared to those from the base model for the current request. Specify a value between 0.0 and 1.0. Unless a different customization weight was specified for the custom model when it was trained, the default value is 0.3. A customization weight that you specify overrides a weight that was specified when the custom model was trained. The default value yields the best performance in general. Assign a higher value if your audio makes frequent use of OOV words from the custom model. Use caution when setting the weight: a higher value can improve the accuracy of phrases from the custom model’s domain, but it can negatively affect performance on non-domain :param str version: The version of the specified base model that is to be used with recognition request or, for the Create a session method, with the new session. Multiple versions of a base model can exist when a model is updated for internal improvements. The parameter is intended primarily for use with custom models that have been upgraded for a new base model. The default value depends on whether the parameter is used with or without a custom model. For more information, see [Base model version](https://console.bluemix.net/docs/services/speech-to-text/input.html#version). phrases. :param int inactivity_timeout: The time in seconds after which, if only silence (no speech) is detected in submitted audio, the connection is closed with a 400 error. Useful for stopping audio submission from a live microphone when a user simply walks away. Use -1 for infinity. :param list[str] keywords: An array of keyword strings to spot in the audio. Each keyword string can include one or more tokens. Keywords are spotted only in the final hypothesis, not in interim results. If you specify any keywords, you must also specify a keywords threshold. You can spot a maximum of 1000 keywords. Omit the parameter or specify an empty array if you do not need to spot keywords. :param float keywords_threshold: A confidence value that is the lower bound for spotting a keyword. A word is considered to match a keyword if its confidence is greater than or equal to the threshold. Specify a probability between 0 and 1 inclusive. No keyword spotting is performed if you omit the parameter. If you specify a threshold, you must also specify one or more keywords. :param int max_alternatives: The maximum number of alternative transcripts to be returned. By default, a single transcription is returned. :param float word_alternatives_threshold: A confidence value that is the lower bound for identifying a hypothesis as a possible word alternative (also known as “Confusion Networks”). An alternative word is considered if its confidence is greater than or equal to the threshold. Specify a probability between 0 and 1 inclusive. No alternative words are computed if you omit the parameter. :param bool word_confidence: If true, a confidence measure in the range of 0 to 1 is returned for each word. By default, no word confidence measures are returned. :param bool timestamps: If true, time alignment is returned for each word. By default, no timestamps are returned. :param bool profanity_filter: If true (the default), filters profanity from all output except for keyword results by replacing inappropriate words with a series of asterisks. Set the parameter to false to return results with no censoring. Applies to US English transcription only. :param bool smart_formatting: If true, converts dates, times, series of digits and numbers, phone numbers, currency values, and internet addresses into more readable, conventional representations in the final transcript of a recognition request. For US English, also converts certain keyword strings to punctuation symbols. By default, no smart formatting is performed. Applies to US English and Spanish transcription only. :param bool speaker_labels: If true, the response includes labels that identify which words were spoken by which participants in a multi-person exchange. By default, no speaker labels are returned. Setting speaker_labels to true forces the timestamps parameter to be true, regardless of whether you specify false for the parameter.

To determine whether a language model supports speaker labels, use the **Get

models** method and check that the attribute speaker_labels is set to true. You can also refer to [Speaker labels](https://console.bluemix.net/docs/services/speech-to-text/output.html#speaker_labels). :param dict headers: A dict containing the request headers :return: A dict containing the RecognitionJob response. :rtype: dict

delete_job(id, **kwargs)

Delete a job.

Deletes the specified job. You cannot delete a job that the service is actively processing. Once you delete a job, its results are no longer available. The service automatically deletes a job and its results when the time to live for the results expires. You must submit the request with the service credentials of the user who created the job.

Parameters:

• id (str) – The ID of the asynchronous job.
• headers (dict) – A dict containing the request headers

Return type:

None

register_callback(callback_url, user_secret=None, **kwargs)

Register a callback.

Registers a callback URL with the service for use with subsequent asynchronous recognition requests. The service attempts to register, or white-list, the callback URL if it is not already registered by sending a GET request to the callback URL. The service passes a random alphanumeric challenge string via the challenge_string parameter of the request. The request includes an Accept header that specifies text/plain as the required response type. To be registered successfully, the callback URL must respond to the GET request from the service. The response must send status code 200 and must include the challenge string in its body. Set the Content-Type response header to text/plain. Upon receiving this response, the service responds to the original registration request with response code 201. The service sends only a single GET request to the callback URL. If the service does not receive a reply with a response code of 200 and a body that echoes the challenge string sent by the service within five seconds, it does not white-list the URL; it instead sends status code 400 in response to the Register a callback request. If the requested callback URL is already white-listed, the service responds to the initial registration request with response code 200. If you specify a user secret with the request, the service uses it as a key to calculate an HMAC-SHA1 signature of the challenge string in its response to the POST request. It sends this signature in the X-Callback-Signature header of its GET request to the URL during registration. It also uses the secret to calculate a signature over the payload of every callback notification that uses the URL. The signature provides authentication and data integrity for HTTP communications. After you successfully register a callback URL, you can use it with an indefinite number of recognition requests. You can register a maximum of 20 callback URLS in a one-hour span of time. For more information, see [Registering a callback URL](https://console.bluemix.net/docs/services/speech-to-text/async.html#register).

Parameters:callback_url (str) – An HTTP or HTTPS URL to which callback notifications are

to be sent. To be white-listed, the URL must successfully echo the challenge string during URL verification. During verification, the client can also check the signature that the service sends in the X-Callback-Signature header to verify the origin of the request. :param str user_secret: A user-specified string that the service uses to generate the HMAC-SHA1 signature that it sends via the X-Callback-Signature header. The service includes the header during URL verification and with every notification sent to the callback URL. It calculates the signature over the payload of the notification. If you omit the parameter, the service does not send the header. :param dict headers: A dict containing the request headers :return: A dict containing the RegisterStatus response. :rtype: dict

unregister_callback(callback_url, **kwargs)

Unregister a callback.

Unregisters a callback URL that was previously white-listed with a Register a callback request for use with the asynchronous interface. Once unregistered, the URL can no longer be used with asynchronous recognition requests.

Parameters:

• callback_url (str) – The callback URL that is to be unregistered.
• headers (dict) – A dict containing the request headers

Return type:

None

create_language_model(name, base_model_name, dialect=None, description=None, **kwargs)

Create a custom language model.

Creates a new custom language model for a specified base model. The custom language model can be used only with the base model for which it is created. The model is owned by the instance of the service whose credentials are used to create it.

Parameters:name (str) – A user-defined name for the new custom language model. Use a name

that is unique among all custom language models that you own. Use a localized name that matches the language of the custom model. Use a name that describes the domain of the custom model, such as Medical custom model or Legal custom model. :param str base_model_name: The name of the base language model that is to be customized by the new custom language model. The new custom model can be used only with the base model that it customizes. To determine whether a base model supports language model customization, request information about the base model and check that the attribute custom_language_model is set to true, or refer to [Language support for customization](https://console.bluemix.net/docs/services/speech-to-text/custom.html#languageSupport). :param str dialect: The dialect of the specified language that is to be used with the custom language model. The parameter is meaningful only for Spanish models, for which the service creates a custom language model that is suited for speech in one of the following dialects: * es-ES for Castilian Spanish (the default) * es-LA for Latin American Spanish * es-US for North American (Mexican) Spanish A specified dialect must be valid for the base model. By default, the dialect matches the language of the base model; for example, en-US for either of the US English language models. :param str description: A description of the new custom language model. Use a localized description that matches the language of the custom model. :param dict headers: A dict containing the request headers :return: A dict containing the LanguageModel response. :rtype: dict

create_custom_model(**kwargs)

delete_language_model(customization_id, **kwargs)

Delete a custom language model.

Deletes an existing custom language model. The custom model cannot be deleted if another request, such as adding a corpus to the model, is currently being processed. You must use credentials for the instance of the service that owns a model to delete it.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param dict headers: A dict containing the request headers :rtype: None

delete_custom_model(**kwargs)

get_language_model(customization_id, **kwargs)

Get a custom language model.

Gets information about a specified custom language model. You must use credentials for the instance of the service that owns a model to list information about it.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param dict headers: A dict containing the request headers :return: A dict containing the LanguageModel response. :rtype: dict

get_custom_model(**kwargs)

list_language_models(language=None, **kwargs)

List custom language models.

Lists information about all custom language models that are owned by an instance of the service. Use the language parameter to see all custom language models for the specified language. Omit the parameter to see all custom language models for all languages. You must use credentials for the instance of the service that owns a model to list information about it.

Parameters:language (str) – The identifier of the language for which custom language or

custom acoustic models are to be returned (for example, en-US). Omit the parameter to see all custom language or custom acoustic models owned by the requesting service credentials. :param dict headers: A dict containing the request headers :return: A dict containing the LanguageModels response. :rtype: dict

list_custom_models(**kwargs)

reset_language_model(customization_id, **kwargs)

Reset a custom language model.

Resets a custom language model by removing all corpora and words from the model. Resetting a custom language model initializes the model to its state when it was first created. Metadata such as the name and language of the model are preserved, but the model’s words resource is removed and must be re-created. You must use credentials for the instance of the service that owns a model to reset it.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param dict headers: A dict containing the request headers :rtype: None

train_language_model(customization_id, word_type_to_add=None, customization_weight=None, **kwargs)

Train a custom language model.

Initiates the training of a custom language model with new corpora, custom words, or both. After adding, modifying, or deleting corpora or words for a custom language model, use this method to begin the actual training of the model on the latest data. You can specify whether the custom language model is to be trained with all words from its words resource or only with words that were added or modified by the user. You must use credentials for the instance of the service that owns a model to train it. The training method is asynchronous. It can take on the order of minutes to complete depending on the amount of data on which the service is being trained and the current load on the service. The method returns an HTTP 200 response code to indicate that the training process has begun. You can monitor the status of the training by using the Get a custom language model method to poll the model’s status. Use a loop to check the status every 10 seconds. The method returns a LanguageModel object that includes status and progress fields. A status of available means that the custom model is trained and ready to use. The service cannot accept subsequent training requests, or requests to add new corpora or words, until the existing request completes. Training can fail to start for the following reasons: * The service is currently handling another request for the custom model, such as another training request or a request to add a corpus or words to the model. * No training data (corpora or words) have been added to the custom model. * One or more words that were added to the custom model have invalid sounds-like pronunciations that you must fix.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str word_type_to_add: The type of words from the custom language model’s words resource on which to train the model: * all (the default) trains the model on all new words, regardless of whether they were extracted from corpora or were added or modified by the user. * user trains the model only on new words that were added or modified by the user; the model is not trained on new words extracted from corpora. :param float customization_weight: Specifies a customization weight for the custom language model. The customization weight tells the service how much weight to give to words from the custom language model compared to those from the base model for speech recognition. Specify a value between 0.0 and 1.0; the default is 0.3. The default value yields the best performance in general. Assign a higher value if your audio makes frequent use of OOV words from the custom model. Use caution when setting the weight: a higher value can improve the accuracy of phrases from the custom model’s domain, but it can negatively affect performance on non-domain phrases. The value that you assign is used for all recognition requests that use the model. You can override it for any recognition request by specifying a customization weight for that request. :param dict headers: A dict containing the request headers :rtype: None

train_custom_model(**kwargs)

upgrade_language_model(customization_id, **kwargs)

Upgrade a custom language model.

Initiates the upgrade of a custom language model to the latest version of its base language model. The upgrade method is asynchronous. It can take on the order of minutes to complete depending on the amount of data in the custom model and the current load on the service. A custom model must be in the ready or available state to be upgraded. You must use credentials for the instance of the service that owns a model to upgrade it. The method returns an HTTP 200 response code to indicate that the upgrade process has begun successfully. You can monitor the status of the upgrade by using the Get a custom language model method to poll the model’s status. The method returns a LanguageModel object that includes status and progress fields. Use a loop to check the status every 10 seconds. While it is being upgraded, the custom model has the status upgrading. When the upgrade is complete, the model resumes the status that it had prior to upgrade. The service cannot accept subsequent requests for the model until the upgrade completes. For more information, see [Upgrading custom models](https://console.bluemix.net/docs/services/speech-to-text/custom-upgrade.html).

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param dict headers: A dict containing the request headers :rtype: None

add_corpus(customization_id, corpus_name, corpus_file, allow_overwrite=None, corpus_file_content_type=None, corpus_filename=None, **kwargs)

Add a corpus.

Adds a single corpus text file of new training data to a custom language model. Use multiple requests to submit multiple corpus text files. You must use credentials for the instance of the service that owns a model to add a corpus to it. Adding a corpus does not affect the custom language model until you train the model for the new data by using the Train a custom language model method. Submit a plain text file that contains sample sentences from the domain of interest to enable the service to extract words in context. The more sentences you add that represent the context in which speakers use words from the domain, the better the service’s recognition accuracy. For guidelines about adding a corpus text file and for information about how the service parses a corpus file, see [Preparing a corpus text file](https://console.bluemix.net/docs/services/speech-to-text/language-resource.html#prepareCorpus). The call returns an HTTP 201 response code if the corpus is valid. The service then asynchronously processes the contents of the corpus and automatically extracts new words that it finds. This can take on the order of a minute or two to complete depending on the total number of words and the number of new words in the corpus, as well as the current load on the service. You cannot submit requests to add additional corpora or words to the custom model, or to train the model, until the service’s analysis of the corpus for the current request completes. Use the List a corpus method to check the status of the analysis. The service auto-populates the model’s words resource with any word that is not found in its base vocabulary; these are referred to as out-of-vocabulary (OOV) words. You can use the List custom words method to examine the words resource, using other words method to eliminate typos and modify how words are pronounced as needed. To add a corpus file that has the same name as an existing corpus, set the allow_overwrite parameter to true; otherwise, the request fails. Overwriting an existing corpus causes the service to process the corpus text file and extract OOV words anew. Before doing so, it removes any OOV words associated with the existing corpus from the model’s words resource unless they were also added by another corpus or they have been modified in some way with the Add custom words or Add a custom word method. The service limits the overall amount of data that you can add to a custom model to a maximum of 10 million total words from all corpora combined. Also, you can add no more than 30 thousand custom (OOV) words to a model; this includes words that the service extracts from corpora and words that you add directly.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str corpus_name: The name of the corpus for the custom language model. When adding a corpus, do not include spaces in the name; use a localized name that matches the language of the custom model; and do not use the name user, which is reserved by the service to denote custom words added or modified by the user. :param file corpus_file: A plain text file that contains the training data for the corpus. Encode the file in UTF-8 if it contains non-ASCII characters; the service assumes UTF-8 encoding if it encounters non-ASCII characters. With cURL, use the –data-binary option to upload the file for the request. :param bool allow_overwrite: If true, the specified corpus or audio resource overwrites an existing corpus or audio resource with the same name. If false (the default), the request fails if a corpus or audio resource with the same name already exists. The parameter has no effect if a corpus or audio resource with the same name does not already exist. :param str corpus_file_content_type: The content type of corpus_file. :param str corpus_filename: The filename for corpus_file. :param dict headers: A dict containing the request headers :rtype: None

delete_corpus(customization_id, corpus_name, **kwargs)

Delete a corpus.

Deletes an existing corpus from a custom language model. The service removes any out-of-vocabulary (OOV) words associated with the corpus from the custom model’s words resource unless they were also added by another corpus or they have been modified in some way with the Add custom words or Add a custom word method. Removing a corpus does not affect the custom model until you train the model with the Train a custom language model method. You must use credentials for the instance of the service that owns a model to delete its corpora.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str corpus_name: The name of the corpus for the custom language model. When adding a corpus, do not include spaces in the name; use a localized name that matches the language of the custom model; and do not use the name user, which is reserved by the service to denote custom words added or modified by the user. :param dict headers: A dict containing the request headers :rtype: None

get_corpus(customization_id, corpus_name, **kwargs)

Get a corpus.

Gets information about a corpus from a custom language model. The information includes the total number of words and out-of-vocabulary (OOV) words, name, and status of the corpus. You must use credentials for the instance of the service that owns a model to list its corpora.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str corpus_name: The name of the corpus for the custom language model. When adding a corpus, do not include spaces in the name; use a localized name that matches the language of the custom model; and do not use the name user, which is reserved by the service to denote custom words added or modified by the user. :param dict headers: A dict containing the request headers :return: A dict containing the Corpus response. :rtype: dict

list_corpora(customization_id, **kwargs)

List corpora.

Lists information about all corpora from a custom language model. The information includes the total number of words and out-of-vocabulary (OOV) words, name, and status of each corpus. You must use credentials for the instance of the service that owns a model to list its corpora.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param dict headers: A dict containing the request headers :return: A dict containing the Corpora response. :rtype: dict

add_word(customization_id, word_name, sounds_like=None, display_as=None, **kwargs)

Add a custom word.

Adds a custom word to a custom language model. The service populates the words resource for a custom model with out-of-vocabulary (OOV) words found in each corpus added to the model. You can use this method to add a word or to modify an existing word in the words resource. The words resource for a model can contain a maximum of 30 thousand custom (OOV) words, including words that the service extracts from corpora and words that you add directly. You must use credentials for the instance of the service that owns a model to add or modify a custom word for the model. Adding or modifying a custom word does not affect the custom model until you train the model for the new data by using the Train a custom language model method. Use the word_name parameter to specify the custom word that is to be added or modified. Use the CustomWord object to provide one or both of the optional sounds_like and display_as fields for the word. * The sounds_like field provides an array of one or more pronunciations for the word. Use the parameter to specify how the word can be pronounced by users. Use the parameter for words that are difficult to pronounce, foreign words, acronyms, and so on. For example, you might specify that the word IEEE can sound like i triple e. You can specify a maximum of five sounds-like pronunciations for a word. For information about pronunciation rules, see [Using the sounds_like field](https://console.bluemix.net/docs/services/speech-to-text/language-resource.html#soundsLike). * The display_as field provides a different way of spelling the word in a transcript. Use the parameter when you want the word to appear different from its usual representation or from its spelling in corpora training data. For example, you might indicate that the word IBM(trademark) is to be displayed as IBM™. For more information, see [Using the display_as field](https://console.bluemix.net/docs/services/speech-to-text/language-resource.html#displayAs). If you add a custom word that already exists in the words resource for the custom model, the new definition overwrites the existing data for the word. If the service encounters an error, it does not add the word to the words resource. Use the List a custom word method to review the word that you add.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str word_name: The custom word for the custom language model. When you add or update a custom word with the Add a custom word method, do not include spaces in the word. Use a - (dash) or _ (underscore) to connect the tokens of compound words. :param list[str] sounds_like: An array of sounds-like pronunciations for the custom word. Specify how words that are difficult to pronounce, foreign words, acronyms, and so on can be pronounced by users. For a word that is not in the service’s base vocabulary, omit the parameter to have the service automatically generate a sounds-like pronunciation for the word. For a word that is in the service’s base vocabulary, use the parameter to specify additional pronunciations for the word. You cannot override the default pronunciation of a word; pronunciations you add augment the pronunciation from the base vocabulary. A word can have at most five sounds-like pronunciations, and a pronunciation can include at most 40 characters not including spaces. :param str display_as: An alternative spelling for the custom word when it appears in a transcript. Use the parameter when you want the word to have a spelling that is different from its usual representation or from its spelling in corpora training data. :param dict headers: A dict containing the request headers :rtype: None

add_custom_word(**kwargs)

add_words(customization_id, words, **kwargs)

Add custom words.

Adds one or more custom words to a custom language model. The service populates the words resource for a custom model with out-of-vocabulary (OOV) words found in each corpus added to the model. You can use this method to add additional words or to modify existing words in the words resource. The words resource for a model can contain a maximum of 30 thousand custom (OOV) words, including words that the service extracts from corpora and words that you add directly. You must use credentials for the instance of the service that owns a model to add or modify custom words for the model. Adding or modifying custom words does not affect the custom model until you train the model for the new data by using the Train a custom language model method. You add custom words by providing a CustomWords object, which is an array of CustomWord objects, one per word. You must use the object’s word parameter to identify the word that is to be added. You can also provide one or both of the optional sounds_like and display_as fields for each word. * The sounds_like field provides an array of one or more pronunciations for the word. Use the parameter to specify how the word can be pronounced by users. Use the parameter for words that are difficult to pronounce, foreign words, acronyms, and so on. For example, you might specify that the word IEEE can sound like i triple e. You can specify a maximum of five sounds-like pronunciations for a word. For information about pronunciation rules, see [Using the sounds_like field](https://console.bluemix.net/docs/services/speech-to-text/language-resource.html#soundsLike). * The display_as field provides a different way of spelling the word in a transcript. Use the parameter when you want the word to appear different from its usual representation or from its spelling in corpora training data. For example, you might indicate that the word IBM(trademark) is to be displayed as IBM™. For more information, see [Using the display_as field](https://console.bluemix.net/docs/services/speech-to-text/language-resource.html#displayAs). If you add a custom word that already exists in the words resource for the custom model, the new definition overwrites the existing data for the word. If the service encounters an error with the input data, it returns a failure code and does not add any of the words to the words resource. The call returns an HTTP 201 response code if the input data is valid. It then asynchronously processes the words to add them to the model’s words resource. The time that it takes for the analysis to complete depends on the number of new words that you add but is generally faster than adding a corpus or training a model. You can monitor the status of the request by using the List a custom language model method to poll the model’s status. Use a loop to check the status every 10 seconds. The method returns a Customization object that includes a status field. A status of ready means that the words have been added to the custom model. The service cannot accept requests to add new corpora or words or to train the model until the existing request completes. You can use the List custom words or List a custom word method to review the words that you add. Words with an invalid sounds_like field include an error field that describes the problem. You can use other words-related methods to correct errors, eliminate typos, and modify how words are pronounced as needed.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param list[CustomWord] words: An array of objects that provides information about each custom word that is to be added to or updated in the custom language model. :param dict headers: A dict containing the request headers :rtype: None

add_custom_words(**kwargs)

delete_word(customization_id, word_name, **kwargs)

Delete a custom word.

Deletes a custom word from a custom language model. You can remove any word that you added to the custom model’s words resource via any means. However, if the word also exists in the service’s base vocabulary, the service removes only the custom pronunciation for the word; the word remains in the base vocabulary. Removing a custom word does not affect the custom model until you train the model with the Train a custom language model method. You must use credentials for the instance of the service that owns a model to delete its words.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str word_name: The custom word for the custom language model. When you add or update a custom word with the Add a custom word method, do not include spaces in the word. Use a - (dash) or _ (underscore) to connect the tokens of compound words. :param dict headers: A dict containing the request headers :rtype: None

delete_custom_word(**kwargs)

get_word(customization_id, word_name, **kwargs)

Get a custom word.

Gets information about a custom word from a custom language model. You must use credentials for the instance of the service that owns a model to query information about its words.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str word_name: The custom word for the custom language model. When you add or update a custom word with the Add a custom word method, do not include spaces in the word. Use a - (dash) or _ (underscore) to connect the tokens of compound words. :param dict headers: A dict containing the request headers :return: A dict containing the Word response. :rtype: dict

get_custom_word(**kwargs)

list_words(customization_id, word_type=None, sort=None, **kwargs)

List custom words.

Lists information about custom words from a custom language model. You can list all words from the custom model’s words resource, only custom words that were added or modified by the user, or only out-of-vocabulary (OOV) words that were extracted from corpora. You can also indicate the order in which the service is to return words; by default, words are listed in ascending alphabetical order. You must use credentials for the instance of the service that owns a model to query information about its words.

Parameters:customization_id (str) – The customization ID (GUID) of the custom language

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str word_type: The type of words to be listed from the custom language model’s words resource: * all (the default) shows all words. * user shows only custom words that were added or modified by the user. * corpora shows only OOV that were extracted from corpora. :param str sort: Indicates the order in which the words are to be listed, alphabetical or by count. You can prepend an optional + or - to an argument to indicate whether the results are to be sorted in ascending or descending order. By default, words are sorted in ascending alphabetical order. For alphabetical ordering, the lexicographical precedence is numeric values, uppercase letters, and lowercase letters. For count ordering, values with the same count are ordered alphabetically. With cURL, URL encode the + symbol as %2B. :param dict headers: A dict containing the request headers :return: A dict containing the Words response. :rtype: dict

list_custom_words(**kwargs)

create_acoustic_model(name, base_model_name, description=None, **kwargs)

Create a custom acoustic model.

Creates a new custom acoustic model for a specified base model. The custom acoustic model can be used only with the base model for which it is created. The model is owned by the instance of the service whose credentials are used to create it.

Parameters:name (str) – A user-defined name for the new custom acoustic model. Use a name

that is unique among all custom acoustic models that you own. Use a localized name that matches the language of the custom model. Use a name that describes the acoustic environment of the custom model, such as Mobile custom model or Noisy car custom model. :param str base_model_name: The name of the base language model that is to be customized by the new custom acoustic model. The new custom model can be used only with the base model that it customizes. To determine whether a base model supports acoustic model customization, refer to [Language support for customization](https://console.bluemix.net/docs/services/speech-to-text/custom.html#languageSupport). :param str description: A description of the new custom acoustic model. Use a localized description that matches the language of the custom model. :param dict headers: A dict containing the request headers :return: A dict containing the AcousticModel response. :rtype: dict

delete_acoustic_model(customization_id, **kwargs)

Delete a custom acoustic model.

Deletes an existing custom acoustic model. The custom model cannot be deleted if another request, such as adding an audio resource to the model, is currently being processed. You must use credentials for the instance of the service that owns a model to delete it.

Parameters:customization_id (str) – The customization ID (GUID) of the custom acoustic

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param dict headers: A dict containing the request headers :rtype: None

get_acoustic_model(customization_id, **kwargs)

Get a custom acoustic model.

Gets information about a specified custom acoustic model. You must use credentials for the instance of the service that owns a model to list information about it.

Parameters:customization_id (str) – The customization ID (GUID) of the custom acoustic

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param dict headers: A dict containing the request headers :return: A dict containing the AcousticModel response. :rtype: dict

list_acoustic_models(language=None, **kwargs)

List custom acoustic models.

Lists information about all custom acoustic models that are owned by an instance of the service. Use the language parameter to see all custom acoustic models for the specified language. Omit the parameter to see all custom acoustic models for all languages. You must use credentials for the instance of the service that owns a model to list information about it.

Parameters:language (str) – The identifier of the language for which custom language or

custom acoustic models are to be returned (for example, en-US). Omit the parameter to see all custom language or custom acoustic models owned by the requesting service credentials. :param dict headers: A dict containing the request headers :return: A dict containing the AcousticModels response. :rtype: dict

reset_acoustic_model(customization_id, **kwargs)

Reset a custom acoustic model.

Resets a custom acoustic model by removing all audio resources from the model. Resetting a custom acoustic model initializes the model to its state when it was first created. Metadata such as the name and language of the model are preserved, but the model’s audio resources are removed and must be re-created. You must use credentials for the instance of the service that owns a model to reset it.

Parameters:customization_id (str) – The customization ID (GUID) of the custom acoustic

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param dict headers: A dict containing the request headers :rtype: None

train_acoustic_model(customization_id, custom_language_model_id=None, **kwargs)

Train a custom acoustic model.

Initiates the training of a custom acoustic model with new or changed audio resources. After adding or deleting audio resources for a custom acoustic model, use this method to begin the actual training of the model on the latest audio data. The custom acoustic model does not reflect its changed data until you train it. You must use credentials for the instance of the service that owns a model to train it. The training method is asynchronous. It can take on the order of minutes or hours to complete depending on the total amount of audio data on which the custom acoustic model is being trained and the current load on the service. Typically, training a custom acoustic model takes approximately two to four times the length of its audio data. The range of time depends on the model being trained and the nature of the audio, such as whether the audio is clean or noisy. The method returns an HTTP 200 response code to indicate that the training process has begun. You can monitor the status of the training by using the Get a custom acoustic model method to poll the model’s status. Use a loop to check the status once a minute. The method returns an AcousticModel object that includes status and progress fields. A status of available indicates that the custom model is trained and ready to use. The service cannot accept subsequent training requests, or requests to add new audio resources, until the existing request completes. You can use the optional custom_language_model_id parameter to specify the GUID of a separately created custom language model that is to be used during training. Specify a custom language model if you have verbatim transcriptions of the audio files that you have added to the custom model or you have either corpora (text files) or a list of words that are relevant to the contents of the audio files. For information about creating a separate custom language model, see [Creating a custom language model](https://console.bluemix.net/docs/services/speech-to-text/language-create.html). Training can fail to start for the following reasons: * The service is currently handling another request for the custom model, such as another training request or a request to add audio resources to the model. * The custom model contains less than 10 minutes or more than 50 hours of audio data. * One or more of the custom model’s audio resources is invalid.

Parameters:customization_id (str) – The customization ID (GUID) of the custom acoustic

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str custom_language_model_id: The customization ID (GUID) of a custom language model that is to be used during training of the custom acoustic model. Specify a custom language model that has been trained with verbatim transcriptions of the audio resources or that contains words that are relevant to the contents of the audio resources. :param dict headers: A dict containing the request headers :rtype: None

upgrade_acoustic_model(customization_id, custom_language_model_id=None, **kwargs)

Upgrade a custom acoustic model.

Initiates the upgrade of a custom acoustic model to the latest version of its base language model. The upgrade method is asynchronous. It can take on the order of minutes or hours to complete depending on the amount of data in the custom model and the current load on the service; typically, upgrade takes approximately twice the length of the total audio contained in the custom model. A custom model must be in the ready or available state to be upgraded. You must use credentials for the instance of the service that owns a model to upgrade it. The method returns an HTTP 200 response code to indicate that the upgrade process has begun successfully. You can monitor the status of the upgrade by using the Get a custom acoustic model method to poll the model’s status. The method returns an AcousticModel object that includes status and progress fields. Use a loop to check the status once a minute. While it is being upgraded, the custom model has the status upgrading. When the upgrade is complete, the model resumes the status that it had prior to upgrade. The service cannot accept subsequent requests for the model until the upgrade completes. If the custom acoustic model was trained with a separately created custom language model, you must use the custom_language_model_id parameter to specify the GUID of that custom language model. The custom language model must be upgraded before the custom acoustic model can be upgraded. Omit the parameter if the custom acoustic model was not trained with a custom language model. For more information, see [Upgrading custom models](https://console.bluemix.net/docs/services/speech-to-text/custom-upgrade.html).

Parameters:customization_id (str) – The customization ID (GUID) of the custom acoustic

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str custom_language_model_id: If the custom acoustic model was trained with a custom language model, the customization ID (GUID) of that custom language model. The custom language model must be upgraded before the custom acoustic model can be upgraded. :param dict headers: A dict containing the request headers :rtype: None

add_audio(customization_id, audio_name, audio_resource, content_type, contained_content_type=None, allow_overwrite=None, **kwargs)

Add an audio resource.

Adds an audio resource to a custom acoustic model. Add audio content that reflects the acoustic characteristics of the audio that you plan to transcribe. You must use credentials for the instance of the service that owns a model to add an audio resource to it. Adding audio data does not affect the custom acoustic model until you train the model for the new data by using the Train a custom acoustic model method. You can add individual audio files or an archive file that contains multiple audio files. Adding multiple audio files via a single archive file is significantly more efficient than adding each file individually. You can add audio resources in any format that the service supports for speech recognition. You can use this method to add any number of audio resources to a custom model by calling the method once for each audio or archive file. But the addition of one audio resource must be fully complete before you can add another. You must add a minimum of 10 minutes and a maximum of 50 hours of audio that includes speech, not just silence, to a custom acoustic model before you can train it. No audio resource, audio- or archive-type, can be larger than 100 MB. To add an audio resource that has the same name as an existing audio resource, set the allow_overwrite parameter to true; otherwise, the request fails. The method is asynchronous. It can take several seconds to complete depending on the duration of the audio and, in the case of an archive file, the total number of audio files being processed. The service returns a 201 response code if the audio is valid. It then asynchronously analyzes the contents of the audio file or files and automatically extracts information about the audio such as its length, sampling rate, and encoding. You cannot submit requests to add additional audio resources to a custom acoustic model, or to train the model, until the service’s analysis of all audio files for the current request completes. To determine the status of the service’s analysis of the audio, use the Get an audio resource method to poll the status of the audio. The method accepts the customization ID of the custom model and the name of the audio resource, and it returns the status of the resource. Use a loop to check the status of the audio every few seconds until it becomes ok. ### Content types for audio-type resources

You can add an individual audio file in any format that the service supports for

speech recognition. For an audio-type resource, use the Content-Type parameter to specify the audio format (MIME type) of the audio file: * audio/basic (Use only with narrowband models.) * audio/flac * audio/l16 (Specify the sampling rate (rate) and optionally the number of channels (channels) and endianness (endianness) of the audio.) * audio/mp3 * audio/mpeg * audio/mulaw (Specify the sampling rate (rate) of the audio.) * audio/ogg (The service automatically detects the codec of the input audio.) * audio/ogg;codecs=opus * audio/ogg;codecs=vorbis * audio/wav (Provide audio with a maximum of nine channels.) * audio/webm (The service automatically detects the codec of the input audio.) * audio/webm;codecs=opus * audio/webm;codecs=vorbis For information about the supported audio formats, including specifying the sampling rate, channels, and endianness for the indicated formats, see [Audio formats](https://console.bluemix.net/docs/services/speech-to-text/audio-formats.html). Note: The sampling rate of an audio file must match the sampling rate of the base model for the custom model: for broadband models, at least 16 kHz; for narrowband models, at least 8 kHz. If the sampling rate of the audio is higher than the minimum required rate, the service down-samples the audio to the appropriate rate. If the sampling rate of the audio is lower than the minimum required rate, the service labels the audio file as invalid. ### Content types for archive-type resources

You can add an archive file (.zip or .tar.gz file) that contains audio

files in any format that the service supports for speech recognition. For an archive-type resource, use the Content-Type parameter to specify the media type of the archive file: * application/zip for a .zip file * application/gzip for a .tar.gz file. All audio files contained in the archive must have the same audio format. Use the Contained-Content-Type parameter to specify the format of the contained audio files. The parameter accepts all of the audio formats supported for use with speech recognition and with the Content-Type header, including the rate, channels, and endianness parameters that are used with some formats. The default contained audio format is audio/wav.

Parameters:customization_id (str) – The customization ID (GUID) of the custom acoustic

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str audio_name: The name of the audio resource for the custom acoustic model. When adding an audio resource, do not include spaces in the name; use a localized name that matches the language of the custom model. :param list[str] audio_resource: The audio resource that is to be added to the custom acoustic model, an individual audio file or an archive file. :param str content_type: The type of the input. :param str contained_content_type: For an archive-type resource, specifies the format of the audio files contained in the archive file. The parameter accepts all of the audio formats supported for use with speech recognition, including the rate, channels, and endianness parameters that are used with some formats. For a complete list of supported audio formats, see [Audio formats](/docs/services/speech-to-text/input.html#formats). :param bool allow_overwrite: If true, the specified corpus or audio resource overwrites an existing corpus or audio resource with the same name. If false (the default), the request fails if a corpus or audio resource with the same name already exists. The parameter has no effect if a corpus or audio resource with the same name does not already exist. :param dict headers: A dict containing the request headers :rtype: None

delete_audio(customization_id, audio_name, **kwargs)

Delete an audio resource.

Deletes an existing audio resource from a custom acoustic model. Deleting an archive-type audio resource removes the entire archive of files; the current interface does not allow deletion of individual files from an archive resource. Removing an audio resource does not affect the custom model until you train the model on its updated data by using the Train a custom acoustic model method. You must use credentials for the instance of the service that owns a model to delete its audio resources.

Parameters:customization_id (str) – The customization ID (GUID) of the custom acoustic

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str audio_name: The name of the audio resource for the custom acoustic model. When adding an audio resource, do not include spaces in the name; use a localized name that matches the language of the custom model. :param dict headers: A dict containing the request headers :rtype: None

get_audio(customization_id, audio_name, **kwargs)

Get an audio resource.

Gets information about an audio resource from a custom acoustic model. The method returns an AudioListing object whose fields depend on the type of audio resource that you specify with the method’s audio_name parameter: * For an audio-type resource, the object’s fields match those of an AudioResource object: duration, name, details, and status. * For an archive-type resource, the object includes a container field whose fields match those of an AudioResource object. It also includes an audio field, which contains an array of AudioResource objects that provides information about the audio files that are contained in the archive. The information includes the status of the specified audio resource. The status is important for checking the service’s analysis of a resource that you add to the custom model. * For an audio-type resource, the status field is located in the AudioListing object. * For an archive-type resource, the status field is located in the AudioResource object that is returned in the container field. You must use credentials for the instance of the service that owns a model to list its audio resources.

Parameters:customization_id (str) – The customization ID (GUID) of the custom acoustic

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param str audio_name: The name of the audio resource for the custom acoustic model. When adding an audio resource, do not include spaces in the name; use a localized name that matches the language of the custom model. :param dict headers: A dict containing the request headers :return: A dict containing the AudioListing response. :rtype: dict

list_audio(customization_id, **kwargs)

List audio resources.

Lists information about all audio resources from a custom acoustic model. The information includes the name of the resource and information about its audio data, such as its duration. It also includes the status of the audio resource, which is important for checking the service’s analysis of the resource in response to a request to add it to the custom acoustic model. You must use credentials for the instance of the service that owns a model to list its audio resources.

Parameters:customization_id (str) – The customization ID (GUID) of the custom acoustic

model. You must make the request with service credentials created for the instance of the service that owns the custom model. :param dict headers: A dict containing the request headers :return: A dict containing the AudioResources response. :rtype: dict

delete_user_data(customer_id, **kwargs)

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. For more information about customer IDs and about using this method, see [Information security](https://console.bluemix.net/docs/services/speech-to-text/information-security.html).

Parameters:

• customer_id (str) – The customer ID for which all data is to be deleted.
• headers (dict) – A dict containing the request headers

Return type:

None

class AcousticModel(customization_id, created=None, language=None, versions=None, owner=None, name=None, description=None, base_model_name=None, status=None, progress=None, warnings=None)

Bases: object

AcousticModel.

Attr str customization_id:  The customization ID (GUID) of the custom acoustic model.

The Create a custom acoustic model method returns only this field of the object; it does not return the other fields. :attr str created: (optional) The date and time in Coordinated Universal Time (UTC) at which the custom acoustic model was created. The value is provided in full ISO 8601 format (YYYY-MM-DDThh:mm:ss.sTZD). :attr str language: (optional) The language identifier of the custom acoustic model (for example, en-US). :attr list[str] versions: (optional) A list of the available versions of the custom acoustic model. Each element of the array indicates a version of the base model with which the custom model can be used. Multiple versions exist only if the custom model has been upgraded; otherwise, only a single version is shown. :attr str owner: (optional) The GUID of the service credentials for the instance of the service that owns the custom acoustic model. :attr str name: (optional) The name of the custom acoustic model. :attr str description: (optional) The description of the custom acoustic model. :attr str base_model_name: (optional) The name of the language model for which the custom acoustic model was created. :attr str status: (optional) The current status of the custom acoustic model: * pending indicates that the model was created but is waiting either for training data to be added or for the service to finish analyzing added data. * ready indicates that the model contains data and is ready to be trained. * training indicates that the model is currently being trained. * available indicates that the model is trained and ready to use. * upgrading indicates that the model is currently being upgraded. * failed indicates that training of the model failed. :attr int progress: (optional) A percentage that indicates the progress of the custom acoustic model’s current training. A value of 100 means that the model is fully trained. Note: The progress field does not currently reflect the progress of the training. The field changes from 0 to 100 when training is complete. :attr str warnings: (optional) If the request included unknown parameters, the following message: Unexpected query parameter(s) [‘parameters’] detected, where parameters is a list that includes a quoted string for each unknown parameter.

class AcousticModels(customizations)

Bases: object

AcousticModels.

Attr list[AcousticModel] customizations:  An array of objects that provides

information about each available custom acoustic model. The array is empty if the requesting service credentials own no custom acoustic models (if no language is specified) or own no custom acoustic models for the specified language.

class AudioDetails(type=None, codec=None, frequency=None, compression=None)

Bases: object

AudioDetails.

Attr str type:(optional) The type of the audio resource:

• audio for an individual audio file
• archive for an archive (.zip or .tar.gz) file that contains audio files
• undetermined for a resource that the service cannot validate (for example, if the

user mistakenly passes a file that does not contain audio, such as a JPEG file). :attr str codec: (optional) For an audio-type resource, the codec in which the audio is encoded. Omitted for an archive-type resource. :attr int frequency: (optional) For an audio-type resource, the sampling rate of the audio in Hertz (samples per second). Omitted for an archive-type resource. :attr str compression: (optional) For an archive-type resource, the format of the compressed archive: * zip for a .zip file * gzip for a .tar.gz file Omitted for an audio-type resource.

class AudioListing(duration=None, name=None, details=None, status=None, container=None, audio=None)

Bases: object

AudioListing.

Attr float duration:  (optional) For an audio-type resource, the total seconds of

audio in the resource. The value is always a whole number. Omitted for an archive-type resource. :attr str name: (optional) For an audio-type resource, the user-specified name of the resource. Omitted for an archive-type resource. :attr AudioDetails details: (optional) For an audio-type resource, an AudioDetails object that provides detailed information about the resource. The object is empty until the service finishes processing the audio. Omitted for an archive-type resource. :attr str status: (optional) For an audio-type resource, the status of the resource: * ok indicates that the service has successfully analyzed the audio data. The data can be used to train the custom model. * being_processed indicates that the service is still analyzing the audio data. The service cannot accept requests to add new audio resources or to train the custom model until its analysis is complete. * invalid indicates that the audio data is not valid for training the custom model (possibly because it has the wrong format or sampling rate, or because it is corrupted). Omitted for an archive-type resource. :attr AudioResource container: (optional) For an archive-type resource, an object of type AudioResource that provides information about the resource. Omitted for an audio-type resource. :attr list[AudioResource] audio: (optional) For an archive-type resource, an array of AudioResource objects that provides information about the audio-type resources that are contained in the resource. Omitted for an audio-type resource.

class AudioResource(duration, name, details, status)

Bases: object

AudioResource.

Attr float duration:  The total seconds of audio in the audio resource. The value is

always a whole number. :attr str name: For an archive-type resource, the user-specified name of the resource. For an audio-type resource, the user-specified name of the resource or the name of the audio file that the user added for the resource. The value depends on the method that is called. :attr AudioDetails details: An AudioDetails object that provides detailed information about the audio resource. The object is empty until the service finishes processing the audio. :attr str status: The status of the audio resource: * ok indicates that the service has successfully analyzed the audio data. The data can be used to train the custom model. * being_processed indicates that the service is still analyzing the audio data. The service cannot accept requests to add new audio resources or to train the custom model until its analysis is complete. * invalid indicates that the audio data is not valid for training the custom model (possibly because it has the wrong format or sampling rate, or because it is corrupted). For an archive file, the entire archive is invalid if any of its audio files are invalid.

class AudioResources(total_minutes_of_audio, audio)

Bases: object

AudioResources.

Attr float total_minutes_of_audio:  The total minutes of accumulated audio summed over

all of the valid audio resources for the custom acoustic model. You can use this value to determine whether the custom model has too little or too much audio to begin training. :attr list[AudioResource] audio: An array of objects that provides information about the audio resources of the custom acoustic model. The array is empty if the custom model has no audio resources.

class Corpora(corpora)

Bases: object

Corpora.

Attr list[Corpus] corpora:  An array of objects that provides information about the

corpora for the custom model. The array is empty if the custom model has no corpora.

class Corpus(name, total_words, out_of_vocabulary_words, status, error=None)

Bases: object

Corpus.

Attr str name:The name of the corpus. Attr int total_words:  The total number of words in the corpus. The value is 0 while

the corpus is being processed. :attr int out_of_vocabulary_words: The number of OOV words in the corpus. The value is 0 while the corpus is being processed. :attr str status: The status of the corpus: * analyzed indicates that the service has successfully analyzed the corpus; the custom model can be trained with data from the corpus. * being_processed indicates that the service is still analyzing the corpus; the service cannot accept requests to add new corpora or words, or to train the custom model. * undetermined indicates that the service encountered an error while processing the corpus. :attr str error: (optional) If the status of the corpus is undetermined, the following message: Analysis of corpus ‘name’ failed. Please try adding the corpus again by setting the ‘allow_overwrite’ flag to ‘true’.

class CustomWord(word=None, sounds_like=None, display_as=None)

Bases: object

CustomWord.

Attr str word:(optional) For the Add custom words method, you must specify the

custom word that is to be added to or updated in the custom model. Do not include spaces in the word. Use a - (dash) or _ (underscore) to connect the tokens of compound words. Omit this field for the Add a custom word method. :attr list[str] sounds_like: (optional) An array of sounds-like pronunciations for the custom word. Specify how words that are difficult to pronounce, foreign words, acronyms, and so on can be pronounced by users. For a word that is not in the service’s base vocabulary, omit the parameter to have the service automatically generate a sounds-like pronunciation for the word. For a word that is in the service’s base vocabulary, use the parameter to specify additional pronunciations for the word. You cannot override the default pronunciation of a word; pronunciations you add augment the pronunciation from the base vocabulary. A word can have at most five sounds-like pronunciations, and a pronunciation can include at most 40 characters not including spaces. :attr str display_as: (optional) An alternative spelling for the custom word when it appears in a transcript. Use the parameter when you want the word to have a spelling that is different from its usual representation or from its spelling in corpora training data.

class KeywordResult(normalized_text, start_time, end_time, confidence)

Bases: object

KeywordResult.

Attr str normalized_text:  A specified keyword normalized to the spoken phrase that

matched in the audio input. :attr float start_time: The start time in seconds of the keyword match. :attr float end_time: The end time in seconds of the keyword match. :attr float confidence: A confidence score for the keyword match in the range of 0 to 1.

class LanguageModel(customization_id, created=None, language=None, dialect=None, versions=None, owner=None, name=None, description=None, base_model_name=None, status=None, progress=None, warnings=None)

Bases: object

LanguageModel.

Attr str customization_id:  The customization ID (GUID) of the custom language model.

The Create a custom language model method returns only this field of the object; it does not return the other fields. :attr str created: (optional) The date and time in Coordinated Universal Time (UTC) at which the custom language model was created. The value is provided in full ISO 8601 format (YYYY-MM-DDThh:mm:ss.sTZD). :attr str language: (optional) The language identifier of the custom language model (for example, en-US). :attr str dialect: (optional) The dialect of the language for the custom language model. By default, the dialect matches the language of the base model; for example, en-US for either of the US English language models. For Spanish models, the field indicates the dialect for which the model was created: * es-ES for Castilian Spanish (the default) * es-LA for Latin American Spanish * es-US for North American (Mexican) Spanish. :attr list[str] versions: (optional) A list of the available versions of the custom language model. Each element of the array indicates a version of the base model with which the custom model can be used. Multiple versions exist only if the custom model has been upgraded; otherwise, only a single version is shown. :attr str owner: (optional) The GUID of the service credentials for the instance of the service that owns the custom language model. :attr str name: (optional) The name of the custom language model. :attr str description: (optional) The description of the custom language model. :attr str base_model_name: (optional) The name of the language model for which the custom language model was created. :attr str status: (optional) The current status of the custom language model: * pending indicates that the model was created but is waiting either for training data to be added or for the service to finish analyzing added data. * ready indicates that the model contains data and is ready to be trained. * training indicates that the model is currently being trained. * available indicates that the model is trained and ready to use. * upgrading indicates that the model is currently being upgraded. * failed indicates that training of the model failed. :attr int progress: (optional) A percentage that indicates the progress of the custom language model’s current training. A value of 100 means that the model is fully trained. Note: The progress field does not currently reflect the progress of the training. The field changes from 0 to 100 when training is complete. :attr str warnings: (optional) If the request included unknown parameters, the following message: Unexpected query parameter(s) [‘parameters’] detected, where parameters is a list that includes a quoted string for each unknown parameter.

class LanguageModels(customizations)

Bases: object

LanguageModels.

Attr list[LanguageModel] customizations:  An array of objects that provides

information about each available custom language model. The array is empty if the requesting service credentials own no custom language models (if no language is specified) or own no custom language models for the specified language.

class RecognitionJob(id, status, created, updated=None, url=None, user_token=None, results=None, warnings=None)

Bases: object

RecognitionJob.

Attr str id:The ID of the asynchronous job. Attr str status:  The current status of the job:

• waiting: The service is preparing the job for processing. The service returns this

status when the job is initially created or when it is waiting for capacity to process the job. The job remains in this state until the service has the capacity to begin processing it. * processing: The service is actively processing the job. * completed: The service has finished processing the job. If the job specified a callback URL and the event recognitions.completed_with_results, the service sent the results with the callback notification; otherwise, you must retrieve the results by checking the individual job. * failed: The job failed. :attr str created: The date and time in Coordinated Universal Time (UTC) at which the job was created. The value is provided in full ISO 8601 format (YYYY-MM-DDThh:mm:ss.sTZD). :attr str updated: (optional) The date and time in Coordinated Universal Time (UTC) at which the job was last updated by the service. The value is provided in full ISO 8601 format (YYYY-MM-DDThh:mm:ss.sTZD). This field is returned only by the Check jobs and Check a job methods. :attr str url: (optional) The URL to use to request information about the job with the Check a job method. This field is returned only by the Create a job method. :attr str user_token: (optional) The user token associated with a job that was created with a callback URL and a user token. This field can be returned only by the Check jobs method. :attr list[SpeechRecognitionResults] results: (optional) If the status is completed, the results of the recognition request as an array that includes a single instance of a SpeechRecognitionResults object. This field is returned only by the Check a job method. :attr list[str] warnings: (optional) An array of warning messages about invalid parameters included with the request. Each warning includes a descriptive message and a list of invalid argument strings, for example, “unexpected query parameter ‘user_token’, query parameter ‘callback_url’ was not specified”. The request succeeds despite the warnings. This field can be returned only by the Create a job method.

class RecognitionJobs(recognitions)

Bases: object

RecognitionJobs.

Attr list[RecognitionJob] recognitions:  An array of objects that provides the status

for each of the user’s current jobs. The array is empty if the user has no current jobs.

class RegisterStatus(status, url)

Bases: object

RegisterStatus.

Attr str status:  The current status of the job:

• created if the callback URL was successfully white-listed as a result of the call.
• already created if the URL was already white-listed.

Attr str url:The callback URL that is successfully registered.

class SpeakerLabelsResult(_from, to, speaker, confidence, final_results)

Bases: object

SpeakerLabelsResult.

Attr float _from:  The start time of a word from the transcript. The value matches the start time of a word from the timestamps array. Attr float to:The end time of a word from the transcript. The value matches the end time of a word from the timestamps array. Attr int speaker:  The numeric identifier that the service assigns to a speaker from the audio. Speaker IDs begin at 0 initially but can evolve and change across interim results (if supported by the method) and between interim and final results as the service processes the audio. They are not guaranteed to be sequential, contiguous, or ordered. Attr float confidence:  A score that indicates the service’s confidence in its identification of the speaker in the range of 0 to 1. Attr bool final_results:  An indication of whether the service might further change word and speaker-label results. A value of true means that the service guarantees not to send any further updates for the current or any preceding results; false means that the service might send further updates to the results.

class SpeechModel(name, language, rate, url, supported_features, description, sessions=None)

Bases: object

SpeechModel.

Attr str name:The name of the model for use as an identifier in calls to the service

(for example, en-US_BroadbandModel). :attr str language: The language identifier of the model (for example, en-US). :attr int rate: The sampling rate (minimum acceptable rate for audio) used by the model in Hertz. :attr str url: The URI for the model. :attr SupportedFeatures supported_features: Describes the additional service features supported with the model. :attr str description: Brief description of the model. :attr str sessions: (optional) The URI for the model for use with the Create a session method. This field is returned only by the Get a model method.

class SpeechModels(models)

Bases: object

SpeechModels.

Attr list[SpeechModel] models:  An array of objects that provides information about

each available model.

class SpeechRecognitionAlternative(transcript, confidence=None, timestamps=None, word_confidence=None)

Bases: object

SpeechRecognitionAlternative.

Attr str transcript:  A transcription of the audio. Attr float confidence:  (optional) A score that indicates the service’s confidence in

the transcript in the range of 0 to 1. Returned only for the best alternative and only with results marked as final. :attr list[str] timestamps: (optional) Time alignments for each word from the transcript as a list of lists. Each inner list consists of three elements: the word followed by its start and end time in seconds. Example: [[“hello”,0.0,1.2],[“world”,1.2,2.5]]. Returned only for the best alternative. :attr list[str] word_confidence: (optional) A confidence score for each word of the transcript as a list of lists. Each inner list consists of two elements: the word and its confidence score in the range of 0 to 1. Example: [[“hello”,0.95],[“world”,0.866]]. Returned only for the best alternative and only with results marked as final.

class SpeechRecognitionResult(final_results, alternatives, keywords_result=None, word_alternatives=None)

Bases: object

SpeechRecognitionResult.

Attr bool final_results:  An indication of whether the transcription results are

final. If true, the results for this utterance are not updated further; no additional results are sent for a result_index once its results are indicated as final. :attr list[SpeechRecognitionAlternative] alternatives: An array of alternative transcripts. The alternatives array can include additional requested output such as word confidence or timestamps. :attr dict keywords_result: (optional) A dictionary (or associative array) whose keys are the strings specified for keywords if both that parameter and keywords_threshold are specified. A keyword for which no matches are found is omitted from the array. The array is omitted if no matches are found for any keywords. :attr list[WordAlternativeResults] word_alternatives: (optional) An array of alternative hypotheses found for words of the input audio if a word_alternatives_threshold is specified.

class SpeechRecognitionResults(results=None, result_index=None, speaker_labels=None, warnings=None)

Bases: object

SpeechRecognitionResults.

Attr list[SpeechRecognitionResult] results:  (optional) An array that can include

interim and final results (interim results are returned only if supported by the method). Final results are guaranteed not to change; interim results might be replaced by further interim results and final results. The service periodically sends updates to the results list; the result_index is set to the lowest index in the array that has changed; it is incremented for new results. :attr int result_index: (optional) An index that indicates a change point in the results array. The service increments the index only for additional results that it sends for new audio for the same request. :attr list[SpeakerLabelsResult] speaker_labels: (optional) An array that identifies which words were spoken by which speakers in a multi-person exchange. Returned in the response only if speaker_labels is true. When interim results are also requested for methods that support them, it is possible for a SpeechRecognitionResults object to include only the speaker_labels field. :attr list[str] warnings: (optional) An array of warning messages associated with the request: * Warnings for invalid parameters or fields can include a descriptive message and a list of invalid argument strings, for example, “Unknown arguments:” or “Unknown url query arguments:” followed by a list of the form “invalid_arg_1, invalid_arg_2.” * The following warning is returned if the request passes a custom model that is based on an older version of a base model for which an updated version is available: “Using previous version of base model, because your custom model has been built with it. Please note that this version will be supported only for a limited time. Consider updating your custom model to the new base model. If you do not do that you will be automatically switched to base model when you used the non-updated custom model.” In both cases, the request succeeds despite the warnings.

class SupportedFeatures(custom_language_model, speaker_labels)

Bases: object

SupportedFeatures.

Attr bool custom_language_model:  Indicates whether the customization interface can be

used to create a custom language model based on the language model. :attr bool speaker_labels: Indicates whether the speaker_labels parameter can be used with the language model.

class Word(word, sounds_like, display_as, count, source, error=None)

Bases: object

Word.

Attr str word:A word from the custom model’s words resource. The spelling of the

word is used to train the model. :attr list[str] sounds_like: An array of pronunciations for the word. The array can include the sounds-like pronunciation automatically generated by the service if none is provided for the word; the service adds this pronunciation when it finishes processing the word. :attr str display_as: The spelling of the word that the service uses to display the word in a transcript. The field contains an empty string if no display-as value is provided for the word, in which case the word is displayed as it is spelled. :attr int count: A sum of the number of times the word is found across all corpora. For example, if the word occurs five times in one corpus and seven times in another, its count is 12. If you add a custom word to a model before it is added by any corpora, the count begins at 1; if the word is added from a corpus first and later modified, the count reflects only the number of times it is found in corpora. :attr list[str] source: An array of sources that describes how the word was added to the custom model’s words resource. For OOV words added from a corpus, includes the name of the corpus; if the word was added by multiple corpora, the names of all corpora are listed. If the word was modified or added by the user directly, the field includes the string user. :attr list[WordError] error: (optional) If the service discovered one or more problems that you need to correct for the word’s definition, an array that describes each of the errors.

class WordAlternativeResult(confidence, word)

Bases: object

WordAlternativeResult.

Attr float confidence:  A confidence score for the word alternative hypothesis in the

range of 0 to 1. :attr str word: An alternative hypothesis for a word from the input audio.

class WordAlternativeResults(start_time, end_time, alternatives)

Bases: object

WordAlternativeResults.

Attr float start_time:  The start time in seconds of the word from the input audio

that corresponds to the word alternatives. :attr float end_time: The end time in seconds of the word from the input audio that corresponds to the word alternatives. :attr list[WordAlternativeResult] alternatives: An array of alternative hypotheses for a word from the input audio.

class WordError(element)

Bases: object

WordError.

Attr str element:  A key-value pair that describes an error associated with the

definition of a word in the words resource. Each pair has the format “element”: “message”, where element is the aspect of the definition that caused the problem and message describes the problem. The following example describes a problem with one of the word’s sounds-like definitions: “{sounds_like_string}”: “Numbers are not allowed in sounds-like. You can try for example ‘{suggested_string}’.” You must correct the error before you can train the model.

class Words(words)

Bases: object

Words.

Attr list[Word] words:  An array of objects that provides information about each word

in the custom model’s words resource. The array is empty if the custom model has no words.