docs: def create_flat_start_model(feature_filename,
                              state_stay_probabilities,
                              symbol_list,
                              output_model_directory,
                              output_prototype_filename,
                              htk_trace):
      """
      Creates a flat start model by using HCompV to compute the global mean and variance.
      Then uses these global mean and variance to create an N-state model for each symbol in the given list.
  
      :param feature_filename: The filename containing the audio and feature file pairs
      :param output_model_directory: The directory where to write the created model
      :param output_prototype_filename: The prototype model filename
      :param htk_trace: Trace level for HTK
      :rtype : None
      """
      # Create a prototype model
      create_prototype_model(feature_filename,
                             output_prototype_filename,
                             state_stay_probabilities=state_stay_probabilities)
  
      # Compute the global mean and variance
      config.htk_command("HCompV -A -D -T {} -f 0.01 "
                         "-S {} -m -o {} -M {} {}".format(htk_trace,
                                                          feature_filename,
                                                          'proto',
                                                          output_model_directory,
                                                          output_prototype_filename))
  
      # Create an hmmdefs using the global mean and variance for all states and symbols
      # Duplicate the model 'proto' -> symbol_list
      proto_model_filename = config.path(output_model_directory, 'proto')
      model = htk.load_model(proto_model_filename)
      model = htk_model_utils.map_hmms(model, {'proto': symbol_list})
  
      # vFloors -> macros
      vfloors_filename = config.path(output_model_directory, 'vFloors')
      variance_model = htk.load_model(vfloors_filename)
  
      model['macros'] += variance_model['macros']
  
      macros, hmmdefs = htk_model_utils.split_model(model)
  
      htk.save_model(macros, config.path(output_model_directory, 'macros'))
      htk.save_model(hmmdefs, config.path(output_model_directory, 'hmmdefs'))