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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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, **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://console.bluemix.net/docs/services/speech-to-text/input.html#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://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 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 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')

        headers = {}
        if self.default_headers is not None:
            headers = self.default_headers.copy()
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))

        if self.token_manager:
            access_token = self.token_manager.get_token()
            headers['Authorization'] = '{0} {1}'.format(BEARER, access_token)
        else:
            authstring = "{0}:{1}".format(self.username, self.password)
            base64_authorization = base64.b64encode(authstring.encode('utf-8')).decode('utf-8')
            headers['Authorization'] = 'Basic {0}'.format(base64_authorization)

        url = self.url.replace('https:', 'wss:')
        params = {
            'model': model,
            'customization_id': customization_id,
            'acoustic_customization_id': acoustic_customization_id,
            'customization_weight': customization_weight,
            'base_model_version': base_model_version,
            'language_customization_id': language_customization_id
        }
        params = dict([(k, v) for k, v in params.items() if v is not None])
        url += '/v1/recognize?{0}'.format(urlencode(params))

        options = {
            '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
        }
        options = dict([(k, v) for k, v in options.items() if v is not None])

        RecognizeListener(audio,
                          options,
                          recognize_callback,
                          url,
                          headers,
                          http_proxy_host,
                          http_proxy_port,
                          self.verify)