Interface RecognizeParams

The customization ID (GUID) of a custom acoustic model that is to be used with the recognition request. The base model of the specified custom acoustic model must match the model specified with the model parameter. You must make the request with credentials for the instance of the service that owns the custom model. By default, no custom acoustic model is used. See Using a custom acoustic model for speech recognition.

The audio to transcribe.

If true, requests detailed information about the signal characteristics of the input audio. The service returns audio metrics with the final transcription results. By default, the service returns no audio metrics.

The level to which the service is to suppress background audio based on its volume to prevent it from being transcribed as speech. Use the parameter to suppress side conversations or background noise.

The version of the specified base model that is to be used with the recognition request. 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. See Making speech recognition requests with upgraded custom models.

The format (MIME type) of the audio. For more information about specifying an audio format, see Audio formats (content types) in the method description.

Deprecated.* Use the language_customization_id parameter to specify the customization ID (GUID) of a custom language model that is to be used with the recognition request. Do not specify both parameters with a request.

If you specify the customization ID (GUID) of a custom language model with the recognition request, 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.

If true, specifies the duration of the pause interval at which the service splits a transcript into multiple final results. If the service detects pauses or extended silence before it reaches the end of the audio stream, its response can include multiple final results. Silence indicates a point at which the speaker pauses between spoken words or phrases.

The name of a grammar that is to be used with the recognition request. If you specify a grammar, you must also use the language_customization_id parameter to specify the name of the custom language model for which the grammar is defined. The service recognizes only strings that are recognized by the specified grammar; it does not recognize other custom words from the model's words resource.

The time in seconds after which, if only silence (no speech) is detected in streaming audio, the connection is closed with a 400 error. The parameter is useful for stopping audio submission from a live microphone when a user simply walks away. Use -1 for infinity. See Inactivity timeout.

An array of keyword strings to spot in the audio. Each keyword string can include one or more string tokens. Keywords are spotted only in the final results, not in interim hypotheses. If you specify any keywords, you must also specify a keywords threshold. Omit the parameter or specify an empty array if you do not need to spot keywords.

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 0.0 and 1.0. If you specify a threshold, you must also specify one or more keywords. The service performs no keyword spotting if you omit either parameter. See Keyword spotting.

The customization ID (GUID) of a custom language model that is to be used with the recognition request. The base model of the specified custom language model must match the model specified with the model parameter. You must make the request with credentials for the instance of the service that owns the custom model. By default, no custom language model is used. See Using a custom language model for speech recognition.

If true for next-generation Multimedia and Telephony models that support low latency, directs the service to produce results even more quickly than it usually does. Next-generation models produce transcription results faster than previous-generation models. The low_latency parameter causes the models to produce results even more quickly, though the results might be less accurate when the parameter is used.

The maximum number of alternative transcripts that the service is to return. By default, the service returns a single transcript. If you specify a value of 0, the service uses the default value, 1. See Maximum alternatives.

The identifier of the model that is to be used for the recognition request. (Note: The model ar-AR_BroadbandModel is deprecated; use ar-MS_BroadbandModel instead.) See Previous-generation languages and models and Next-generation languages and models.

If true, the service 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 and Japanese transcription only. See Profanity filtering.

If true, the service redacts, or masks, numeric data from final transcripts. The feature redacts any number that has three or more consecutive digits by replacing each digit with an X character. It is intended to redact sensitive numeric data, such as credit card numbers. By default, the service performs no redaction.

If true, the service 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, the service also converts certain keyword strings to punctuation symbols. By default, the service performs no smart formatting.

If true, the response includes labels that identify which words were spoken by which participants in a multi-person exchange. By default, the service returns no speaker labels. Setting speaker_labels to true forces the timestamps parameter to be true, regardless of whether you specify false for the parameter.

The sensitivity of speech activity detection that the service is to perform. Use the parameter to suppress word insertions from music, coughing, and other non-speech events. The service biases the audio it passes for speech recognition by evaluating the input audio against prior models of speech and non-speech activity.

If true, directs the service to split the transcript into multiple final results based on semantic features of the input, for example, at the conclusion of meaningful phrases such as sentences. The service bases its understanding of semantic features on the base language model that you use with a request. Custom language models and grammars can also influence how and where the service splits a transcript. By default, the service splits transcripts based solely on the pause interval.

If true, the service returns time alignment for each word. By default, no timestamps are returned. See Word timestamps.

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 0.0 and 1.0. By default, the service computes no alternative words. See Word alternatives.

If true, the service returns a confidence measure in the range of 0.0 to 1.0 for each word. By default, the service returns no word confidence scores. See Word confidence.