def recognize_using_websocket(self,
audio,
content_type,
recognize_callback,
model=None,
language_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,
customization_id=None,
grammar_name=None,
redaction=None,
processing_metrics=None,
processing_metrics_interval=None,
audio_metrics=None,
**kwargs):
"""
Sends audio for speech recognition using web sockets.
:param AudioSource 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 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 language_customization_id: 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 service credentials created for
the instance of the service that owns the custom model. By default, no custom
language model is used. See [Custom
models](https://cloud.ibm.com/docs/services/speech-to-text?topic=speech-to-text-input#custom).
**Note:** Use this parameter instead of the deprecated `customization_id`
parameter.
: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://cloud.ibm.com/docs/services/speech-to-text?topic=speech-to-text-input#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://cloud.ibm.com/docs/services/speech-to-text?topic=speech-to-text-output#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 str customization_id: **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.
:param str grammar_name: 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. See
[Grammars](https://cloud.ibm.com/docs/services/speech-to-text/output.html).
:param bool redaction: 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.
When you enable redaction, the service automatically enables smart formatting,
regardless of whether you explicitly disable that feature. To ensure maximum
security, the service also disables keyword spotting (ignores the `keywords` and
`keywords_threshold` parameters) and returns only a single final transcript
(forces the `max_alternatives` parameter to be `1`).
**Note:** Applies to US English, Japanese, and Korean transcription only.
See [Numeric
redaction](https://cloud.ibm.com/docs/services/speech-to-text/output.html#redaction).
:param bool processing_metrics: If `true`, requests processing metrics about the
service's transcription of the input audio. The service returns processing metrics
at the interval specified by the `processing_metrics_interval` parameter. It also
returns processing metrics for transcription events, for example, for final and
interim results. By default, the service returns no processing metrics.
:param float processing_metrics_interval: Specifies the interval in real
wall-clock seconds at which the service is to return processing metrics. The
parameter is ignored unless the `processing_metrics` parameter is set to `true`.
The parameter accepts a minimum value of 0.1 seconds. The level of precision is
not restricted, so you can specify values such as 0.25 and 0.125.
The service does not impose a maximum value. If you want to receive processing
metrics only for transcription events instead of at periodic intervals, set the
value to a large number. If the value is larger than the duration of the audio,
the service returns processing metrics only for transcription events.
:param bool audio_metrics: 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.
:param dict headers: A `dict` containing the request headers
:return: A `dict` containing the `SpeechRecognitionResults` response.
:rtype: dict
"""
if audio is None:
raise ValueError('audio must be provided')
if not isinstance(audio, AudioSource):
raise Exception(
'audio is not of type AudioSource. Import the class from ibm_watson.websocket'
)
if content_type is None:
raise ValueError('content_type must be provided')
if recognize_callback is None:
raise ValueError('recognize_callback must be provided')
if not isinstance(recognize_callback, RecognizeCallback):
raise Exception(
'Callback is not a derived class of RecognizeCallback')
request = {}
headers = {}
if self.default_headers is not None:
headers = self.default_headers.copy()
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
request['headers'] = headers
if self.authenticator:
self.authenticator.authenticate(request)
url = self.service_url.replace('https:', 'wss:')
params = {
'model': model,
'customization_id': customization_id,
'acoustic_customization_id': acoustic_customization_id,
'base_model_version': base_model_version,
'language_customization_id': language_customization_id
}
params = {k: v for k, v in params.items() if v is not None}
url += '/v1/recognize?{0}'.format(urlencode(params))
request['url'] = url
options = {
'customization_weight': customization_weight,
'content_type': content_type,
'inactivity_timeout': inactivity_timeout,
'interim_results': interim_results,
'keywords': keywords,
'keywords_threshold': keywords_threshold,
'max_alternatives': max_alternatives,
'word_alternatives_threshold': word_alternatives_threshold,
'word_confidence': word_confidence,
'timestamps': timestamps,
'profanity_filter': profanity_filter,
'smart_formatting': smart_formatting,
'speaker_labels': speaker_labels,
'grammar_name': grammar_name,
'redaction': redaction,
'processing_metrics': processing_metrics,
'processing_metrics_interval': processing_metrics_interval,
'audio_metrics': audio_metrics
}
options = {k: v for k, v in options.items() if v is not None}
request['options'] = options
RecognizeListener(audio, request.get('options'), recognize_callback,
request.get('url'), request.get('headers'),
http_proxy_host, http_proxy_port,
self.disable_ssl_verification)
def recognize_using_websocket(self,
audio,
content_type,
recognize_callback,
model=None,
language_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,
customization_id=None,
grammar_name=None,
redaction=None,
processing_metrics=None,
processing_metrics_interval=None,
audio_metrics=None,
end_of_phrase_silence_time=None,
split_transcript_at_phrase_end=None,
speech_detector_sensitivity=None,
background_audio_suppression=None,
low_latency=None,
**kwargs):
"""
Sends audio for speech recognition using web sockets.
:param AudioSource 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 RecognizeCallback recognize_callback: The callback method for the websocket.
:param str model: (optional) 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 [Languages and
models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models)
and [Next-generation languages and
models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng).
:param str language_customization_id: (optional) 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](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageUse).
**Note:** Use this parameter instead of the deprecated `customization_id`
parameter.
:param str acoustic_customization_id: (optional) 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](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-acousticUse).
:param str base_model_version: (optional) 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](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-upgrade-use#custom-upgrade-use-recognition).
:param float customization_weight: (optional) 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.
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.
See [Using customization
weight](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageUse#weight).
:param int inactivity_timeout: (optional) 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](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-input#timeouts-inactivity).
:param List[str] keywords: (optional) 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.
You can spot a maximum of 1000 keywords with a single request. A single
keyword can have a maximum length of 1024 characters, though the maximum
effective length for double-byte languages might be shorter. Keywords are
case-insensitive.
See [Keyword
spotting](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-spotting#keyword-spotting).
:param float keywords_threshold: (optional) 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](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-spotting#keyword-spotting).
:param int max_alternatives: (optional) 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](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metadata#max-alternatives).
:param float word_alternatives_threshold: (optional) 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](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-spotting#word-alternatives).
:param bool word_confidence: (optional) 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](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metadata#word-confidence).
:param bool timestamps: (optional) If `true`, the service returns time
alignment for each word. By default, no timestamps are returned. See [Word
timestamps](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metadata#word-timestamps).
:param bool profanity_filter: (optional) 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](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-formatting#profanity-filtering).
:param bool smart_formatting: (optional) 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.
**Note:** Applies to US English, Japanese, and Spanish transcription only.
See [Smart
formatting](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-formatting#smart-formatting).
:param bool speaker_labels: (optional) 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.
* For previous-generation models, can be used for US English, Australian
English, German, Japanese, Korean, and Spanish (both broadband and
narrowband models) and UK English (narrowband model) transcription only.
* For next-generation models, can be used for English (Australian, UK, and
US), German, and Spanish transcription only.
Restrictions and limitations apply to the use of speaker labels for both
types of models. See [Speaker
labels](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-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 str customization_id: (optional) **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.
:param str grammar_name: (optional) 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. See
[Using a grammar for speech
recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-grammarUse).
:param bool redaction: (optional) 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.
When you enable redaction, the service automatically enables smart
formatting, regardless of whether you explicitly disable that feature. To
ensure maximum security, the service also disables keyword spotting
(ignores the `keywords` and `keywords_threshold` parameters) and returns
only a single final transcript (forces the `max_alternatives` parameter to
be `1`).
**Note:** Applies to US English, Japanese, and Korean transcription only.
See [Numeric
redaction](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-formatting#numeric-redaction).
:param bool audio_metrics: (optional) 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.
See [Audio
metrics](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metrics#audio-metrics).
:param float end_of_phrase_silence_time: (optional) 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.
Specify a value for the pause interval in the range of 0.0 to 120.0.
* A value greater than 0 specifies the interval that the service is to use
for speech recognition.
* A value of 0 indicates that the service is to use the default interval.
It is equivalent to omitting the parameter.
The default pause interval for most languages is 0.8 seconds; the default
for Chinese is 0.6 seconds.
See [End of phrase silence
time](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-parsing#silence-time).
:param bool split_transcript_at_phrase_end: (optional) 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.
See [Split transcript at phrase
end](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-parsing#split-transcript).
:param float speech_detector_sensitivity: (optional) 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.
Specify a value between 0.0 and 1.0:
* 0.0 suppresses all audio (no speech is transcribed).
* 0.5 (the default) provides a reasonable compromise for the level of
sensitivity.
* 1.0 suppresses no audio (speech detection sensitivity is disabled).
The values increase on a monotonic curve. See [Speech detector
sensitivity](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-detection#detection-parameters-sensitivity).
:param float background_audio_suppression: (optional) 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.
Specify a value in the range of 0.0 to 1.0:
* 0.0 (the default) provides no suppression (background audio suppression
is disabled).
* 0.5 provides a reasonable level of audio suppression for general usage.
* 1.0 suppresses all audio (no audio is transcribed).
The values increase on a monotonic curve. See [Background audio
suppression](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-detection#detection-parameters-suppression).
:param bool low_latency: (optional) 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.
**Note:** The parameter is beta functionality. It is not available for
previous-generation `Broadband` and `Narrowband` models. It is available
only for some next-generation models.
* For a list of next-generation models that support low latency, see
[Supported language
models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng#models-ng-supported)
for next-generation models.
* For more information about the `low_latency` parameter, see [Low
latency](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-interim#low-latency).
:param dict headers: A `dict` containing the request headers
:return: A `dict` containing the `SpeechRecognitionResults` response.
:rtype: dict
"""
if audio is None:
raise ValueError('audio must be provided')
if not isinstance(audio, AudioSource):
raise Exception(
'audio is not of type AudioSource. Import the class from ibm_watson.websocket'
)
if content_type is None:
raise ValueError('content_type must be provided')
if recognize_callback is None:
raise ValueError('recognize_callback must be provided')
if not isinstance(recognize_callback, RecognizeCallback):
raise Exception(
'Callback is not a derived class of RecognizeCallback')
request = {}
headers = {}
if self.default_headers is not None:
headers = self.default_headers.copy()
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
request['headers'] = headers
if self.authenticator:
self.authenticator.authenticate(request)
url = self.service_url.replace('https:', 'wss:')
params = {
'model': model,
'customization_id': customization_id,
'acoustic_customization_id': acoustic_customization_id,
'base_model_version': base_model_version,
'language_customization_id': language_customization_id
}
params = {k: v for k, v in params.items() if v is not None}
url += '/v1/recognize?{0}'.format(urlencode(params))
request['url'] = url
options = {
'customization_weight': customization_weight,
'content_type': content_type,
'inactivity_timeout': inactivity_timeout,
'interim_results': interim_results,
'keywords': keywords,
'keywords_threshold': keywords_threshold,
'max_alternatives': max_alternatives,
'word_alternatives_threshold': word_alternatives_threshold,
'word_confidence': word_confidence,
'timestamps': timestamps,
'profanity_filter': profanity_filter,
'smart_formatting': smart_formatting,
'speaker_labels': speaker_labels,
'grammar_name': grammar_name,
'redaction': redaction,
'processing_metrics': processing_metrics,
'processing_metrics_interval': processing_metrics_interval,
'audio_metrics': audio_metrics,
'end_of_phrase_silence_time': end_of_phrase_silence_time,
'split_transcript_at_phrase_end': split_transcript_at_phrase_end,
'speech_detector_sensitivity': speech_detector_sensitivity,
'background_audio_suppression': background_audio_suppression,
'low_latency': low_latency
}
options = {k: v for k, v in options.items() if v is not None}
request['options'] = options
RecognizeListener(audio, request.get('options'), recognize_callback,
request.get('url'), request.get('headers'),
http_proxy_host, http_proxy_port,
self.disable_ssl_verification)