import os
import functools
from Word import Word
from video_to_audio import AudioFile

def delete_audio_after_use(transcribe_func):
  @functools.wraps(transcribe_func)
  def wrapper(*args):
    assert isinstance(args[1], AudioFile), "Please pass the AudioFile object returned from 'to_raw_audio()'."
    assert args[1].file_path is not None, "This file already transcribed and deleted."
    assert isinstance(args[2], bool), "Please pass the temp_status returned from 'to_raw_audio()'."

    output = transcribe_func(args[0], args[1].file_path)

    # cleaning the mess
    args[1].delete(args[2])

    return output
  return wrapper

'''
Speech Recognition implemented using the recent Pocketsphinx class
RFC 5646 language tag to initialize the recognizer
'''
class SphinxRecognizer_PS():
  def __init__(self, language='en-US'):
    self.Pocketsphinx = __import__('pocketsphinx').Pocketsphinx
    self.language = language

    self.data_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'pocketsphinx-data', self.language)
    self.acoustic_parameters_directory = os.path.join(self.data_directory, 'acoustic-model')
    self.language_model_directory = os.path.join(self.data_directory, 'language-model.lm.bin')
    self.phoneme_dict_directory = os.path.join(self.data_directory, 'pronounciation-dictionary.dict')

  '''
  Transcribes the give audio file
  Returns a list of Word object.
  '''
  @delete_audio_after_use
  def transcribe(self, audio_file: str) -> list:
    FPS = 100       # default frames per second
    config = {
      'hmm': os.path.join(self.data_directory, self.acoustic_parameters_directory),
      'lm': os.path.join(self.data_directory, self.language_model_directory),
      'dict': os.path.join(self.data_directory, self.phoneme_dict_directory)
    }

    ps = self.Pocketsphinx(**config)
    ps.decode(
      audio_file = os.path.join('temp', audio_file),
      no_search = False,
      full_utt = False
    )

    segments = ps.segments(detailed=True)
    if len(segments) == 0:
      raise Exception("Couldn't transcribe.")

    return [Word(w[0], w[2]/FPS, w[3]/FPS) for w in segments]
6075cf7f3ec557e9e410f6d3039c95dbd491aa36
<mask token>


class SphinxRecognizer_PS:

    def __init__(self, language='en-US'):
        self.Pocketsphinx = __import__('pocketsphinx').Pocketsphinx
        self.language = language
        self.data_directory = os.path.join(os.path.dirname(os.path.realpath
            (__file__)), 'pocketsphinx-data', self.language)
        self.acoustic_parameters_directory = os.path.join(self.
            data_directory, 'acoustic-model')
        self.language_model_directory = os.path.join(self.data_directory,
            'language-model.lm.bin')
        self.phoneme_dict_directory = os.path.join(self.data_directory,
            'pronounciation-dictionary.dict')
    <mask token>

    @delete_audio_after_use
    def transcribe(self, audio_file: str) ->list:
        FPS = 100
        config = {'hmm': os.path.join(self.data_directory, self.
            acoustic_parameters_directory), 'lm': os.path.join(self.
            data_directory, self.language_model_directory), 'dict': os.path
            .join(self.data_directory, self.phoneme_dict_directory)}
        ps = self.Pocketsphinx(**config)
        ps.decode(audio_file=os.path.join('temp', audio_file), no_search=
            False, full_utt=False)
        segments = ps.segments(detailed=True)
        if len(segments) == 0:
            raise Exception("Couldn't transcribe.")
        return [Word(w[0], w[2] / FPS, w[3] / FPS) for w in segments]

<mask token>


class SphinxRecognizer_PS:

    def __init__(self, language='en-US'):
        self.Pocketsphinx = __import__('pocketsphinx').Pocketsphinx
        self.language = language
        self.data_directory = os.path.join(os.path.dirname(os.path.realpath
            (__file__)), 'pocketsphinx-data', self.language)
        self.acoustic_parameters_directory = os.path.join(self.
            data_directory, 'acoustic-model')
        self.language_model_directory = os.path.join(self.data_directory,
            'language-model.lm.bin')
        self.phoneme_dict_directory = os.path.join(self.data_directory,
            'pronounciation-dictionary.dict')
    """
  Transcribes the give audio file
  Returns a list of Word object.
  """

    @delete_audio_after_use
    def transcribe(self, audio_file: str) ->list:
        FPS = 100
        config = {'hmm': os.path.join(self.data_directory, self.
            acoustic_parameters_directory), 'lm': os.path.join(self.
            data_directory, self.language_model_directory), 'dict': os.path
            .join(self.data_directory, self.phoneme_dict_directory)}
        ps = self.Pocketsphinx(**config)
        ps.decode(audio_file=os.path.join('temp', audio_file), no_search=
            False, full_utt=False)
        segments = ps.segments(detailed=True)
        if len(segments) == 0:
            raise Exception("Couldn't transcribe.")
        return [Word(w[0], w[2] / FPS, w[3] / FPS) for w in segments]

<mask token>


def delete_audio_after_use(transcribe_func):

    @functools.wraps(transcribe_func)
    def wrapper(*args):
        assert isinstance(args[1], AudioFile
            ), "Please pass the AudioFile object returned from 'to_raw_audio()'."
        assert args[1
            ].file_path is not None, 'This file already transcribed and deleted.'
        assert isinstance(args[2], bool
            ), "Please pass the temp_status returned from 'to_raw_audio()'."
        output = transcribe_func(args[0], args[1].file_path)
        args[1].delete(args[2])
        return output
    return wrapper


<mask token>


class SphinxRecognizer_PS:

    def __init__(self, language='en-US'):
        self.Pocketsphinx = __import__('pocketsphinx').Pocketsphinx
        self.language = language
        self.data_directory = os.path.join(os.path.dirname(os.path.realpath
            (__file__)), 'pocketsphinx-data', self.language)
        self.acoustic_parameters_directory = os.path.join(self.
            data_directory, 'acoustic-model')
        self.language_model_directory = os.path.join(self.data_directory,
            'language-model.lm.bin')
        self.phoneme_dict_directory = os.path.join(self.data_directory,
            'pronounciation-dictionary.dict')
    """
  Transcribes the give audio file
  Returns a list of Word object.
  """

    @delete_audio_after_use
    def transcribe(self, audio_file: str) ->list:
        FPS = 100
        config = {'hmm': os.path.join(self.data_directory, self.
            acoustic_parameters_directory), 'lm': os.path.join(self.
            data_directory, self.language_model_directory), 'dict': os.path
            .join(self.data_directory, self.phoneme_dict_directory)}
        ps = self.Pocketsphinx(**config)
        ps.decode(audio_file=os.path.join('temp', audio_file), no_search=
            False, full_utt=False)
        segments = ps.segments(detailed=True)
        if len(segments) == 0:
            raise Exception("Couldn't transcribe.")
        return [Word(w[0], w[2] / FPS, w[3] / FPS) for w in segments]

import os
import functools
from Word import Word
from video_to_audio import AudioFile


def delete_audio_after_use(transcribe_func):

    @functools.wraps(transcribe_func)
    def wrapper(*args):
        assert isinstance(args[1], AudioFile
            ), "Please pass the AudioFile object returned from 'to_raw_audio()'."
        assert args[1
            ].file_path is not None, 'This file already transcribed and deleted.'
        assert isinstance(args[2], bool
            ), "Please pass the temp_status returned from 'to_raw_audio()'."
        output = transcribe_func(args[0], args[1].file_path)
        args[1].delete(args[2])
        return output
    return wrapper


<mask token>


class SphinxRecognizer_PS:

    def __init__(self, language='en-US'):
        self.Pocketsphinx = __import__('pocketsphinx').Pocketsphinx
        self.language = language
        self.data_directory = os.path.join(os.path.dirname(os.path.realpath
            (__file__)), 'pocketsphinx-data', self.language)
        self.acoustic_parameters_directory = os.path.join(self.
            data_directory, 'acoustic-model')
        self.language_model_directory = os.path.join(self.data_directory,
            'language-model.lm.bin')
        self.phoneme_dict_directory = os.path.join(self.data_directory,
            'pronounciation-dictionary.dict')
    """
  Transcribes the give audio file
  Returns a list of Word object.
  """

    @delete_audio_after_use
    def transcribe(self, audio_file: str) ->list:
        FPS = 100
        config = {'hmm': os.path.join(self.data_directory, self.
            acoustic_parameters_directory), 'lm': os.path.join(self.
            data_directory, self.language_model_directory), 'dict': os.path
            .join(self.data_directory, self.phoneme_dict_directory)}
        ps = self.Pocketsphinx(**config)
        ps.decode(audio_file=os.path.join('temp', audio_file), no_search=
            False, full_utt=False)
        segments = ps.segments(detailed=True)
        if len(segments) == 0:
            raise Exception("Couldn't transcribe.")
        return [Word(w[0], w[2] / FPS, w[3] / FPS) for w in segments]

import os
import functools
from Word import Word
from video_to_audio import AudioFile

def delete_audio_after_use(transcribe_func):
  @functools.wraps(transcribe_func)
  def wrapper(*args):
    assert isinstance(args[1], AudioFile), "Please pass the AudioFile object returned from 'to_raw_audio()'."
    assert args[1].file_path is not None, "This file already transcribed and deleted."
    assert isinstance(args[2], bool), "Please pass the temp_status returned from 'to_raw_audio()'."

    output = transcribe_func(args[0], args[1].file_path)

    # cleaning the mess
    args[1].delete(args[2])

    return output
  return wrapper

'''
Speech Recognition implemented using the recent Pocketsphinx class
RFC 5646 language tag to initialize the recognizer
'''
class SphinxRecognizer_PS():
  def __init__(self, language='en-US'):
    self.Pocketsphinx = __import__('pocketsphinx').Pocketsphinx
    self.language = language

    self.data_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'pocketsphinx-data', self.language)
    self.acoustic_parameters_directory = os.path.join(self.data_directory, 'acoustic-model')
    self.language_model_directory = os.path.join(self.data_directory, 'language-model.lm.bin')
    self.phoneme_dict_directory = os.path.join(self.data_directory, 'pronounciation-dictionary.dict')

  '''
  Transcribes the give audio file
  Returns a list of Word object.
  '''
  @delete_audio_after_use
  def transcribe(self, audio_file: str) -> list:
    FPS = 100       # default frames per second
    config = {
      'hmm': os.path.join(self.data_directory, self.acoustic_parameters_directory),
      'lm': os.path.join(self.data_directory, self.language_model_directory),
      'dict': os.path.join(self.data_directory, self.phoneme_dict_directory)
    }

    ps = self.Pocketsphinx(**config)
    ps.decode(
      audio_file = os.path.join('temp', audio_file),
      no_search = False,
      full_utt = False
    )

    segments = ps.segments(detailed=True)
    if len(segments) == 0:
      raise Exception("Couldn't transcribe.")

    return [Word(w[0], w[2]/FPS, w[3]/FPS) for w in segments]