old_contents: #!/usr/bin/env python
  
  # Copyright 2018 Google LLC
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #      http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  """Google Cloud Speech API sample that demonstrates enhanced models
  and recognition metadata.
  
  Example usage:
      python transcribe_enhanced_model.py resources/commercial_mono.wav
  """
  
  import argparse
  
  
  def transcribe_file_with_enhanced_model(path):
      """Transcribe the given audio file using an enhanced model."""
      # [START speech_transcribe_enhanced_model]
      import io
  
      from google.cloud import speech
  
      client = speech.SpeechClient()
  
      # path = 'resources/commercial_mono.wav'
      with io.open(path, "rb") as audio_file:
          content = audio_file.read()
  
      audio = speech.RecognitionAudio(content=content)
      config = speech.RecognitionConfig(
          encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
          sample_rate_hertz=8000,
          language_code="en-US",
          # Enhanced models are only available to projects that
          # opt in for audio data collection.
          use_enhanced=True,
          # A model must be specified to use enhanced model.
          model="phone_call",
      )
  
      response = client.recognize(config=config, audio=audio)
  
      for i, result in enumerate(response.results):
          alternative = result.alternatives[0]
          print("-" * 20)
          print("First alternative of result {}".format(i))
          print("Transcript: {}".format(alternative.transcript))
      # [END speech_transcribe_enhanced_model]
  
  
  if __name__ == "__main__":
      parser = argparse.ArgumentParser(
          description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
      )
      parser.add_argument("path", help="File to stream to the API")
  
      args = parser.parse_args()
  
      transcribe_file_with_enhanced_model(args.path)
  
new_contents: #!/usr/bin/env python
  
  # Copyright 2018 Google LLC
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #      http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  """Google Cloud Speech API sample that demonstrates enhanced models
  and recognition metadata.
  
  Example usage:
      python transcribe_enhanced_model.py resources/commercial_mono.wav
  """
  
  import argparse
  
  
  def transcribe_file_with_enhanced_model(path):
      """Transcribe the given audio file using an enhanced model."""
      # [START speech_transcribe_enhanced_model]
      import io
  
      from google.cloud import speech
  
      client = speech.SpeechClient()
  
      # path = 'resources/commercial_mono.wav'
      with io.open(path, "rb") as audio_file:
          content = audio_file.read()
  
      audio = speech.RecognitionAudio(content=content)
      config = speech.RecognitionConfig(
          encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
          sample_rate_hertz=8000,
          language_code="en-US",
          use_enhanced=True,
          # A model must be specified to use enhanced model.
          model="phone_call",
      )
  
      response = client.recognize(config=config, audio=audio)
  
      for i, result in enumerate(response.results):
          alternative = result.alternatives[0]
          print("-" * 20)
          print("First alternative of result {}".format(i))
          print("Transcript: {}".format(alternative.transcript))
      # [END speech_transcribe_enhanced_model]
  
  
  if __name__ == "__main__":
      parser = argparse.ArgumentParser(
          description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
      )
      parser.add_argument("path", help="File to stream to the API")
  
      args = parser.parse_args()
  
      transcribe_file_with_enhanced_model(args.path)
  
subject: Remove incorrect comment on enhanced models (#95)