Construct a SpeechToTextV1 object.
| Name | Type | Attribute | Description |
|---|---|---|---|
options |
UserOptions |
Options for the service. |
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. You can add multiple different audio resources at the same time. You must add a minimum of
10 minutes and a maximum of 200 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 or minutes 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 train or upgrade the model until the service's analysis of all audio resources for current requests 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.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also: Add audio to the custom acoustic model.
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,
including specifying the sampling rate, channels, and endianness where indicated.
audio/alaw (Specify the sampling rate (rate) of the audio.)audio/basic (Use only with narrowband models.)audio/flacaudio/g729 (Use only with narrowband models.)audio/l16 (Specify the sampling rate (rate) and optionally the number of channels (channels) and endianness
(endianness) of the audio.)audio/mp3audio/mpegaudio/mulaw (Specify the sampling rate (rate) of the audio.)audio/ogg (The service automatically detects the codec of the input audio.)audio/ogg;codecs=opusaudio/ogg;codecs=vorbisaudio/wav (Provide audio with a maximum of nine channels.)audio/webm (The service automatically detects the codec of the input audio.)audio/webm;codecs=opusaudio/webm;codecs=vorbisThe 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.
See also: Supported audio formats.
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 fileapplication/gzip for a .tar.gz file.When you add an archive-type resource, the Contained-Content-Type header is optional depending on the format of
the files that you are adding:
audio/alaw, audio/basic, audio/l16, or audio/mulaw, you must use the
Contained-Content-Type header to specify the format of the contained audio files. Include the rate, channels,
and endianness parameters where necessary. In this case, all audio files contained in the archive file must have
the same audio format.Contained-Content-Type header. In this case, the audio
files contained in the archive file can have any of the formats not listed in the previous bullet. The audio files
do not need to have the same format.Do not use the Contained-Content-Type header when adding an audio-type resource.
The name of an audio file that is contained in an archive-type resource can include a maximum of 128 characters. This includes the file extension and all elements of the name (for example, slashes).
| Name | Type | Attribute | Description | ||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
AddAudioParams |
The parameters to send to the service. Properties
|
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 parse the 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.
The call returns an HTTP 201 response code if the corpus is valid. The service then asynchronously processes and automatically extracts data from the contents of the corpus. This operation can take on the order of minutes to complete depending on the current load on the service, the total number of words in the corpus, and, _for custom models that are based on previous-generation models_, the number of new (out-of-vocabulary) words in the corpus. You cannot submit requests to add additional resources to the custom model or to train the model until the service's analysis of the corpus for the current request completes. Use the Get a corpus method to check the status of the analysis.
_For custom models that are based on previous-generation models_, the service auto-populates the model's words resource with words from the corpus that are not found in its base vocabulary. These words are referred to as out-of-vocabulary (OOV) words. After adding a corpus, you must validate the words resource to ensure that each OOV word's definition is complete and valid. You can use the List custom words method to examine the words resource. You can use 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 its data anew. _For a custom model that is based on a previous-generation model_, the service first removes
any OOV words that are associated with the existing corpus from the model's words resource unless they were also
added by another corpus or grammar, 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 sources combined. _For a custom model that is based on a previous-generation model_, you can add no more than 90 thousand custom (OOV) words to a model. This includes words that the service extracts from corpora and grammars, and words that you add directly.
See also:
| Name | Type | Attribute | Description | ||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
AddCorpusParams |
The parameters to send to the service. Properties
|
Add a grammar.
Adds a single grammar file to a custom language model. Submit a plain text file in UTF-8 format that defines the grammar. Use multiple requests to submit multiple grammar files. You must use credentials for the instance of the service that owns a model to add a grammar to it. Adding a grammar 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.
The call returns an HTTP 201 response code if the grammar is valid. The service then asynchronously processes the contents of the grammar and automatically extracts new words that it finds. This operation can take a few seconds or minutes to complete depending on the size and complexity of the grammar, as well as the current load on the service. You cannot submit requests to add additional resources to the custom model or to train the model until the service's analysis of the grammar for the current request completes. Use the Get a grammar method to check the status of the analysis.
The service populates the model's words resource with any word that is recognized by the grammar that is not found in the model's 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 and use other words-related methods to eliminate typos and modify how words are pronounced as needed.
To add a grammar that has the same name as an existing grammar, set the allow_overwrite parameter to true;
otherwise, the request fails. Overwriting an existing grammar causes the service to process the grammar file and
extract OOV words anew. Before doing so, it removes any OOV words associated with the existing grammar from the
model's words resource unless they were also added by another resource 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 sources combined. Also, you can add no more than 90 thousand OOV words to a model. This includes words that the service extracts from corpora and grammars and words that you add directly. Grammars are available for all languages and models that support language customization.
Note: Grammars are supported only for use with previous-generation models. They are not supported for next-generation models.
See also:
| Name | Type | Attribute | Description | ||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
AddGrammarParams |
The parameters to send to the service. Properties
|
Add a custom word.
Adds a custom word to a custom language model. You can use this method to add a word or to modify an existing word in the words resource. _For custom models that are based on previous-generation models_, the service populates the words resource for a custom model with out-of-vocabulary (OOV) words from each corpus or grammar that is added to the model. You can use this method to modify OOV words in the model's words resource.
_For a custom model that is based on a previous-generation models_, the words resource for a model can contain a maximum of 90 thousand custom (OOV) words. This includes words that the service extracts from corpora and grammars 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 display_as or sounds_like fields for the word.
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 training data. For example,
you might indicate that the word IBM is to be displayed as IBM™.sounds_like field, _which can be used only with a custom model that is based on a previous-generation
model_, 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. If you omit the sounds_like field, the service attempts to set the
field to its pronunciation of the word. It cannot generate a pronunciation for all words, so you must review the
word's definition to ensure that it is complete and valid.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 Get a custom word method to review the word that you add.
See also:
| Name | Type | Attribute | Description | ||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
AddWordParams |
The parameters to send to the service. Properties
|
Add custom words.
Adds one or more custom words to a custom language model. You can use this method to add words or to modify existing words in a custom model's words resource. _For custom models that are based on previous-generation models_, the service populates the words resource for a custom model with out-of-vocabulary (OOV) words from each corpus or grammar that is added to the model. You can use this method to modify OOV words in the model's words resource.
_For a custom model that is based on a previous-generation model_, the words resource for a model can contain a maximum of 90 thousand custom (OOV) words. This includes words that the service extracts from corpora and grammars 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.
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 display_as or sounds_like fields for each word.
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 training data. For example,
you might indicate that the word IBM is to be displayed as IBM™.sounds_like field, _which can be used only with a custom model that is based on a previous-generation
model_, 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. If you omit the sounds_like field, the service attempts to set the
field to its pronunciation of the word. It cannot generate a pronunciation for all words, so you must review the
word's definition to ensure that it is complete and valid.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 grammar.
You can monitor the status of the request 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 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 data or to train the model until the existing request
completes.
You can use the List custom words or Get 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.
See also:
| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
AddWordsParams |
The parameters to send to the service. Properties
|
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 use credentials for the instance of the service that owns a job to list information about it.
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 credentials.
See also: Checking the status and retrieving the results of a job.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
CheckJobParams |
The parameters to send to the service. Properties
|
Check jobs.
Returns the ID and status of the latest 100 outstanding jobs associated with the 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[(#checkjob) 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.
See also: Checking the status of the latest jobs.
| Name | Type | Attribute | Description | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
params |
CheckJobsParams | Optional |
Properties
|
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.
You can create a maximum of 1024 custom acoustic models per owning credentials. The service returns an error if you attempt to create more than 1024 models. You do not lose any models, but you cannot create any more until your model count is below the limit.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also: Create a custom acoustic model.
| Name | Type | Attribute | Description | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
CreateAcousticModelParams |
The parameters to send to the service. Properties
|
Create a job.
Creates a job for a new asynchronous recognition request. The job is owned by the instance of the service whose 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:
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.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. 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. It also supports the following parameters specific to the asynchronous interface:
callback_urleventsuser_tokenresults_ttlYou can pass a maximum of 1 GB and a minimum of 100 bytes of audio with a request. The service automatically
detects the endianness of the incoming audio and, for audio that includes multiple channels, downmixes the audio to
one-channel mono during transcoding. The method returns only final results; to enable interim results, use the
WebSocket API. (With the curl command, use the --data-binary option to upload the file for the request.)
See also: Creating a job.
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 service closes the connection (status code 408) if it does
not receive at least 15 seconds of audio (including silence) in any 30-second period. The service also closes the
connection (status code 400) if it detects no speech for inactivity_timeout seconds of streaming audio; use the
inactivity_timeout parameter to change the default of 30 seconds.
See also:
The service accepts audio in the following formats (MIME types).
Content-Type header with the request to specify the
format of the audio.Content-Type header or specify application/octet-stream with the
header to have the service automatically detect the format of the audio. (With the curl command, you can specify
either "Content-Type:" or "Content-Type: application/octet-stream".)Where indicated, the format that you specify must include the sampling rate and can optionally include the number of channels and the endianness of the audio.
audio/alaw (Required. Specify the sampling rate (rate) of the audio.)audio/basic (Required. Use only with narrowband models.)audio/flacaudio/g729 (Use only with narrowband models.)audio/l16 (Required. Specify the sampling rate (rate) and optionally the number of channels (channels)
and endianness (endianness) of the audio.)audio/mp3audio/mpegaudio/mulaw (Required. Specify the sampling rate (rate) of the audio.)audio/ogg (The service automatically detects the codec of the input audio.)audio/ogg;codecs=opusaudio/ogg;codecs=vorbisaudio/wav (Provide audio with a maximum of nine channels.)audio/webm (The service automatically detects the codec of the input audio.)audio/webm;codecs=opusaudio/webm;codecs=vorbisThe sampling rate of the audio must match the sampling rate of the model for the recognition request: 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 request fails.
See also: Supported audio formats.
The service supports next-generation Multimedia (16 kHz) and Telephony (8 kHz) models for many languages.
Next-generation models have higher throughput than the service's previous generation of Broadband and
Narrowband models. When you use next-generation models, the service can return transcriptions more quickly and
also provide noticeably better transcription accuracy.
You specify a next-generation model by using the model query parameter, as you do a previous-generation model.
Many next-generation models also support the low_latency parameter, which is not available with
previous-generation models.
But next-generation models do not support all of the parameters that are available for use with previous-generation models. For more information about all parameters that are supported for use with next-generation models, see Supported features for next-generation models.
See also: Next-generation languages and models.
| Name | Type | Attribute | Description | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
CreateJobParams |
The parameters to send to the service. Properties
|
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.
You can create a maximum of 1024 custom language models per owning credentials. The service returns an error if you attempt to create more than 1024 models. You do not lose any models, but you cannot create any more until your model count is below the limit.
See also: Create a custom language model.
| Name | Type | Attribute | Description | ||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
CreateLanguageModelParams |
The parameters to send to the service. Properties
|
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.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also: Deleting a custom acoustic model.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
DeleteAcousticModelParams |
The parameters to send to the service. Properties
|
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 service 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 can delete an existing audio resource from a model while a different resource is being added to the model. You must use credentials for the instance of the service that owns a model to delete its audio resources.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also: Deleting an audio resource from a custom acoustic model.
| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
DeleteAudioParams |
The parameters to send to the service. Properties
|
Delete a corpus.
Deletes an existing corpus from a custom language model. 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.
_For custom models that are based on previous-generation models_, the service removes any out-of-vocabulary (OOV) words that are associated with the corpus from the custom model's words resource unless they were also added by another corpus or grammar, or they were modified in some way with the Add custom words or Add a custom word method.
| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
DeleteCorpusParams |
The parameters to send to the service. Properties
|
Delete a grammar.
Deletes an existing grammar from a custom language model. The service removes any out-of-vocabulary (OOV) words associated with the grammar from the custom model's words resource unless they were also added by another resource or they were modified in some way with the Add custom words or Add a custom word method. Removing a grammar 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 grammar. Grammars are available for all languages and models that support language customization.
Note: Grammars are supported only for use with previous-generation models. They are not supported for next-generation models.
| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
DeleteGrammarParams |
The parameters to send to the service. Properties
|
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 use credentials for the instance of the service that owns a job to delete it.
See also: Deleting a job.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
DeleteJobParams |
The parameters to send to the service. Properties
|
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 or grammar to the model, is currently being processed. You must use credentials for the instance of the service that owns a model to delete it.
See also: Deleting a custom language model.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
DeleteLanguageModelParams |
The parameters to send to the service. Properties
|
Delete labeled data.
Deletes all data that is associated with a specified customer ID. The method deletes all data for the customer ID,
regardless of the method by which the information was added. The method has no effect if no data is associated with
the customer ID. You must issue the request with credentials for the same instance of the service that was used to
associate the customer ID with the data. You associate a customer ID with data by passing the X-Watson-Metadata
header with a request that passes the data.
Note: If you delete an instance of the service from the service console, all data associated with that service instance is automatically deleted. This includes all custom language models, corpora, grammars, and words; all custom acoustic models and audio resources; all registered endpoints for the asynchronous HTTP interface; and all data related to speech recognition requests.
See also: Information security.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
DeleteUserDataParams |
The parameters to send to the service. Properties
|
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 the word only from the words resource; 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.
See also: Deleting a word from a custom language model.
| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
DeleteWordParams |
The parameters to send to the service. Properties
|
Disables retries.
Enable retries for unfulfilled requests.
| Name | Type | Attribute | Description |
|---|---|---|---|
retryOptions |
RetryOptions | Optional |
configuration for retries |
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.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also: Listing custom acoustic models.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
GetAcousticModelParams |
The parameters to send to the service. Properties
|
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:
AudioResource object: duration, name,
details, and status.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.
status field is located in the AudioListing object.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.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also: Listing audio resources for a custom acoustic model.
| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
GetAudioParams |
The parameters to send to the service. Properties
|
Get the instance of the authenticator set on the service.
Get a corpus.
Gets information about a corpus from a custom language model. The information includes the name, status, and total number of words for the corpus. _For custom models that are based on previous-generation models_, it also includes the number of out-of-vocabulary (OOV) words from the corpus. You must use credentials for the instance of the service that owns a model to list its corpora.
See also: Listing corpora for a custom language model.
| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
GetCorpusParams |
The parameters to send to the service. Properties
|
Get a grammar.
Gets information about a grammar from a custom language model. The information includes the total number of out-of-vocabulary (OOV) words, name, and status of the grammar. You must use credentials for the instance of the service that owns a model to list its grammars. Grammars are available for all languages and models that support language customization.
Note: Grammars are supported only for use with previous-generation models. They are not supported for next-generation models.
| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
GetGrammarParams |
The parameters to send to the service. Properties
|
Get the Axios instance set on the service. All requests will be made using this instance.
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.
See also: Listing custom language models.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
GetLanguageModelParams |
The parameters to send to the service. Properties
|
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.
See also: Listing models.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
GetModelParams |
The parameters to send to the service. Properties
|
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 list information about its words.
See also: Listing words from a custom language model.
| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
GetWordParams |
The parameters to send to the service. Properties
|
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.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also: Listing custom acoustic models.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
ListAcousticModelsParams | Optional |
Properties
|
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.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also: Listing audio resources for a custom acoustic model.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
ListAudioParams |
The parameters to send to the service. Properties
|
List corpora.
Lists information about all corpora from a custom language model. The information includes the name, status, and total number of words for each corpus. _For custom models that are based on previous-generation models_, it also includes the number of out-of-vocabulary (OOV) words from the corpus. You must use credentials for the instance of the service that owns a model to list its corpora.
See also: Listing corpora for a custom language model.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
ListCorporaParams |
The parameters to send to the service. Properties
|
List grammars.
Lists information about all grammars from a custom language model. The information includes the total number of out-of-vocabulary (OOV) words, name, and status of each grammar. You must use credentials for the instance of the service that owns a model to list its grammars. Grammars are available for all languages and models that support language customization.
Note: Grammars are supported only for use with previous-generation models. They are not supported for next-generation models.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
ListGrammarsParams |
The parameters to send to the service. Properties
|
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.
See also: Listing custom language models.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
ListLanguageModelsParams | Optional |
Properties
|
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. The ordering of the list of models can change from call to call; do not rely on an alphabetized or static list of models.
See also: Listing models.
| Name | Type | Attribute | Description | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
params |
ListModelsParams | Optional |
Properties
|
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, _for a custom model that is based on a previous-generation model_, only out-of-vocabulary (OOV) words that were extracted from corpora or are recognized by grammars. You can also indicate the order in which the service is to return words; by default, the service lists words in ascending alphabetical order. You must use credentials for the instance of the service that owns a model to list information about its words.
See also: Listing words from a custom language model.
| Name | Type | Attribute | Description | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
ListWordsParams |
The parameters to send to the service. Properties
|
Recognize audio.
Sends audio and returns transcription results for a recognition request. You can pass a maximum of 100 MB and a
minimum of 100 bytes of audio with a request. The service automatically detects the endianness of the incoming
audio and, for audio that includes multiple channels, downmixes the audio to one-channel mono during transcoding.
The method returns only final results; to enable interim results, use the WebSocket API. (With the curl command,
use the --data-binary option to upload the file for the request.)
See also: Making a basic HTTP request.
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 service closes the connection (status code 408) if it does
not receive at least 15 seconds of audio (including silence) in any 30-second period. The service also closes the
connection (status code 400) if it detects no speech for inactivity_timeout seconds of streaming audio; use the
inactivity_timeout parameter to change the default of 30 seconds.
See also:
The service accepts audio in the following formats (MIME types).
Content-Type header with the request to specify the
format of the audio.Content-Type header or specify application/octet-stream with the
header to have the service automatically detect the format of the audio. (With the curl command, you can specify
either "Content-Type:" or "Content-Type: application/octet-stream".)Where indicated, the format that you specify must include the sampling rate and can optionally include the number of channels and the endianness of the audio.
audio/alaw (Required. Specify the sampling rate (rate) of the audio.)audio/basic (Required. Use only with narrowband models.)audio/flacaudio/g729 (Use only with narrowband models.)audio/l16 (Required. Specify the sampling rate (rate) and optionally the number of channels (channels)
and endianness (endianness) of the audio.)audio/mp3audio/mpegaudio/mulaw (Required. Specify the sampling rate (rate) of the audio.)audio/ogg (The service automatically detects the codec of the input audio.)audio/ogg;codecs=opusaudio/ogg;codecs=vorbisaudio/wav (Provide audio with a maximum of nine channels.)audio/webm (The service automatically detects the codec of the input audio.)audio/webm;codecs=opusaudio/webm;codecs=vorbisThe sampling rate of the audio must match the sampling rate of the model for the recognition request: 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 request fails.
See also: Supported audio formats.
The service supports next-generation Multimedia (16 kHz) and Telephony (8 kHz) models for many languages.
Next-generation models have higher throughput than the service's previous generation of Broadband and
Narrowband models. When you use next-generation models, the service can return transcriptions more quickly and
also provide noticeably better transcription accuracy.
You specify a next-generation model by using the model query parameter, as you do a previous-generation model.
Many next-generation models also support the low_latency parameter, which is not available with
previous-generation models.
But next-generation models do not support all of the parameters that are available for use with previous-generation models. For more information about all parameters that are supported for use with next-generation models, see Supported features for next-generation models.
See also: Next-generation languages and models.
Note: The Watson SDKs do not support multipart speech recognition.
The HTTP POST method of the service also supports multipart speech recognition. 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. You can use multipart recognition to
pass multiple audio files with a single request.
Use the multipart approach 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.
See also: Making a multipart HTTP request.
| Name | Type | Attribute | Description | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
RecognizeParams |
The parameters to send to the service. Properties
|
Register a callback.
Registers a callback URL with the service for use with subsequent asynchronous recognition requests. The service
attempts to register, or allowlist, 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 allowlist the URL; it instead sends status code 400 in response to the request to register a callback. If the
requested callback URL is already allowlisted, 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.
See also: Registering a callback URL.
| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
RegisterCallbackParams |
The parameters to send to the service. Properties
|
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. The service cannot reset a model while it is handling another request for the model. The service cannot accept subsequent requests for the model until the existing reset request completes. You must use credentials for the instance of the service that owns a model to reset it.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also: Resetting a custom acoustic model.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
ResetAcousticModelParams |
The parameters to send to the service. Properties
|
Reset a custom language model.
Resets a custom language model by removing all corpora, grammars, 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.
See also: Resetting a custom language model.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
ResetLanguageModelParams |
The parameters to send to the service. Properties
|
Turn request body compression on or off.
| Name | Type | Attribute | Description |
|---|---|---|---|
setting |
boolean |
Will turn it on if 'true', off if 'false'. |
Set the service URL to send requests to.
| Name | Type | Attribute | Description |
|---|---|---|---|
url |
string |
The base URL for the service. |
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. Training time depends on the cumulative amount of audio data that the custom acoustic model contains and the current load on the service. When you train or retrain a model, the service uses all of the model's audio data in the training. Training a custom acoustic model takes approximately as long as the length of its cumulative audio data. For example, it takes approximately 2 hours to train a model that contains a total of 2 hours of audio. 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 train a model while it is handling another request for the model. The service
cannot accept subsequent training requests, or requests to add new audio resources, until the existing training
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. Train with 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 training to succeed, both of the
custom models must be based on the same version of the same base model, and the custom language model must be fully
trained and available.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also:
Training can fail to start for the following reasons:
custom_language_model_id query parameter that is not in the
available state. A custom language model must be fully trained and available to be used to train a custom acoustic
model.custom_language_model_id query parameter. Both custom
models must be based on the same version of the same base model.strict parameter to false to exclude the invalid resources from the training. The model must contain at
least one valid resource for training to succeed.| Name | Type | Attribute | Description | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
TrainAcousticModelParams |
The parameters to send to the service. Properties
|
Train a custom language model.
Initiates the training of a custom language model with new resources such as corpora, grammars, and custom words. After adding, modifying, or deleting resources 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 directly. 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 resources until the
existing request completes.
See also: Train the custom language model.
Training can fail to start for the following reasons:
strict parameter to false
to exclude the invalid resources from the training. The model must contain at least one valid resource for training
to succeed.| Name | Type | Attribute | Description | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
TrainLanguageModelParams |
The parameters to send to the service. Properties
|
Unregister a callback.
Unregisters a callback URL that was previously allowlisted 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.
See also: Unregistering a callback URL.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
UnregisterCallbackParams |
The parameters to send to the service. Properties
|
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 upgrade
a model while it is handling another request for the model. The service cannot accept subsequent requests for the
model until the existing upgrade request 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.
Note: Acoustic model customization is supported only for use with previous-generation models. It is not supported for next-generation models.
See also: Upgrading a custom acoustic model.
| Name | Type | Attribute | Description | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
UpgradeAcousticModelParams |
The parameters to send to the service. Properties
|
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.
Note: Upgrading is necessary only for custom language models that are based on previous-generation models. Only a single version of a custom model that is based on a next-generation model is ever available.
See also: Upgrading a custom language model.
| Name | Type | Attribute | Description | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
params |
UpgradeLanguageModelParams |
The parameters to send to the service. Properties
|
Generated using TypeDoc
The IBM Watson™ Speech to Text service provides APIs that use IBM's speech-recognition capabilities to produce transcripts of spoken audio. The service can transcribe speech from various languages and audio formats. In addition to basic transcription, the service can produce detailed information about many different aspects of the audio. It returns all JSON response content in the UTF-8 character set. interfaces
The service supports two types of models: previous-generation models that include the terms
BroadbandandNarrowbandin their names, and next-generation models that include the termsMultimediaandTelephonyin their names. Broadband and multimedia models have minimum sampling rates of 16 kHz. Narrowband and telephony models have minimum sampling rates of 8 kHz. The next-generation models offer high throughput and greater transcription accuracy.For speech recognition, the service supports synchronous and asynchronous HTTP Representational State Transfer (REST) interfaces. It also supports a WebSocket interface that provides a full-duplex, low-latency communication channel: Clients send requests and audio to the service and receive results over a single connection asynchronously.
The service also offers two customization interfaces. 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. For language model customization, the service also supports grammars. A grammar is a formal language specification that lets you restrict the phrases that the service can recognize.
Language model customization is available for most previous- and next-generation models. Acoustic model customization is available for all previous-generation models. Grammars are beta functionality that is available for all previous-generation models that support language model customization.
API Version: 1.0.0 See: https://cloud.ibm.com/docs/speech-to-text