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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 _index_audio_ibm(self, basename=None, replace_already_indexed=False, continuous=True, model="en-US_BroadbandModel", word_confidence=True, word_alternatives_threshold=0.9, profanity_filter_for_US_results=False):
 """ Implements a search-suitable interface for Watson speech API. Some explaination of the parameters here have been taken from [1]_ Parameters basename : str, optional A specific basename to be indexed and is placed in src_dir e.g `audio.wav`. If `None` is selected, all the valid audio files would be indexed. Default is `None`. replace_already_indexed : bool `True`, To reindex some audio file that's already in the timestamps. Default is `False`. continuous : bool Indicates whether multiple final results that represent consecutive phrases separated by long pauses are returned. If true, such phrases are returned; if false (the default), recognition ends after the first end-of-speech (EOS) incident is detected. Default is `True`. model : { 'ar-AR_BroadbandModel', 'en-UK_BroadbandModel' 'en-UK_NarrowbandModel', 'en-US_BroadbandModel', (the default) 'en-US_NarrowbandModel', 'es-ES_BroadbandModel', 'es-ES_NarrowbandModel', 'fr-FR_BroadbandModel', 'ja-JP_BroadbandModel', 'ja-JP_NarrowbandModel', 'pt-BR_BroadbandModel', 'pt-BR_NarrowbandModel', 'zh-CN_BroadbandModel', 'zh-CN_NarrowbandModel' } The identifier of the model to be used for the recognition Default is 'en-US_BroadbandModel' word_confidence : bool Indicates whether a confidence measure in the range of 0 to 1 is returned for each word. The default is True. (It's False in the original) word_alternatives_threshold : numeric 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. Default is `0.9`. profanity_filter_for_US_results : bool Indicates whether profanity filtering is performed on the transcript. If true, the service filters profanity from all output by replacing inappropriate words with a series of asterisks. If false, the service returns results with no censoring. Applies to US English transcription only. Default is `False`. References .. [1] : https://ibm.com/watson/developercloud/speech-to-text/api/v1/ """

        params = {'continuous': continuous,
                  'model': model,
                  'word_alternatives_threshold': word_alternatives_threshold,
                  'word_confidence': word_confidence,
                  'timestamps': True,
                  'inactivity_timeout': str(-1),
                  'profanity_filter': profanity_filter_for_US_results}

        self._prepare_audio(basename=basename,
                            replace_already_indexed=replace_already_indexed)

        for staging_audio_basename in self._list_audio_files(
                sub_dir="staging"):
            original_audio_name = ''.join(
                staging_audio_basename.split('.')[:-1])[:-3]
            with open("{}/staging/{}".format(
                    self.src_dir, staging_audio_basename), "rb") as f:
                if self.get_verbosity():
                    print("Uploading {}...".format(staging_audio_basename))
                response = requests.post(
                    url=("https://stream.watsonplatform.net/"
                         "speech-to-text/api/v1/recognize"),
                    auth=(self.get_username_ibm(), self.get_password_ibm()),
                    headers={'content-type': 'audio/wav'},
                    data=f.read(),
                    params=params)
                if self.get_verbosity():
                    print("Indexing {}...".format(staging_audio_basename))
                self.__timestamps_unregulated[
                    original_audio_name + ".wav"].append(
                        self._timestamp_extractor_ibm(
                            staging_audio_basename, json.loads(response.text)))
                if self.get_verbosity():
                    print("Done indexing {}".format(staging_audio_basename))
        self._timestamp_regulator()

        if self.get_verbosity():
            print("Indexing procedure finished")