watson_developer_cloud.speech_to_text_v1_adapter module

class SpeechToTextV1Adapter(url='https://stream.watsonplatform.net/speech-to-text/api', username=None, password=None, iam_apikey=None, iam_access_token=None, iam_url=None)

Bases: watson_developer_cloud.speech_to_text_v1.SpeechToTextV1

recognize_using_websocket(audio, content_type, recognize_callback, model=None, customization_id=None, acoustic_customization_id=None, customization_weight=None, base_model_version=None, inactivity_timeout=None, interim_results=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, http_proxy_host=None, http_proxy_port=None, **kwargs)

Sends audio for speech recognition using web sockets.

Parameters:audio (AudioSource) – 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 RecognizeCallback recognize_callback: The callback method for the websocket. :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 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 base_model_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 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 str http_proxy_host: http proxy host name. :param str http_proxy_port: http proxy port. If not set, set to 80. :param dict headers: A dict containing the request headers :return: A dict containing the SpeechRecognitionResults response. :rtype: dict

add_corpus(customization_id, corpus_name, corpus_file, allow_overwrite=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 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 :return: A DetailedResponse containing the result, headers and HTTP status code. :rtype: DetailedResponse