🚧[WIP/TEST] Model : 文字起こし起動時にエンジンを選択するように変更
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2
model.py
2
model.py
@@ -341,6 +341,7 @@ class Model:
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source=self.mic_audio_recorder.source,
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phrase_timeout=phase_timeout,
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max_phrases=config.INPUT_MIC_MAX_PHRASES,
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transcription_engine=config.SELECTED_TRANSCRIPTION_ENGINE,
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root=config.PATH_LOCAL,
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whisper_weight_type=config.WHISPER_WEIGHT_TYPE,
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)
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@@ -443,6 +444,7 @@ class Model:
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source=self.speaker_audio_recorder.source,
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phrase_timeout=phase_timeout,
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max_phrases=config.INPUT_SPEAKER_MAX_PHRASES,
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transcription_engine=config.SELECTED_TRANSCRIPTION_ENGINE,
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root=config.PATH_LOCAL,
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whisper_weight_type=config.WHISPER_WEIGHT_TYPE,
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)
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@@ -14,13 +14,15 @@ PHRASE_TIMEOUT = 3
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MAX_PHRASES = 10
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class AudioTranscriber:
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def __init__(self, speaker, source, phrase_timeout, max_phrases, root=None, whisper_weight_type=None, ):
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def __init__(self, speaker, source, phrase_timeout, max_phrases, transcription_engine, root=None, whisper_weight_type=None):
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self.speaker = speaker
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self.phrase_timeout = phrase_timeout
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self.max_phrases = max_phrases
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self.transcript_data = []
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self.transcript_changed_event = Event()
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self.audio_recognizer = Recognizer()
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self.transcription_engine = "Google"
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self.whisper_model = None
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self.audio_sources = {
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"sample_rate": source.SAMPLE_RATE,
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"sample_width": source.SAMPLE_WIDTH,
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@@ -30,10 +32,10 @@ class AudioTranscriber:
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"new_phrase": True,
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"process_data_func": self.processSpeakerData if speaker else self.processSpeakerData
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}
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if whisper_weight_type is not None and root is not None and checkWhisperWeight(root, whisper_weight_type) is True:
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if transcription_engine == "Whisper" and checkWhisperWeight(root, whisper_weight_type) is True:
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self.whisper_model = getWhisperModel(root, whisper_weight_type)
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else:
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self.whisper_model = None
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self.transcription_engine = "Whisper"
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def transcribeAudioQueue(self, audio_queue, language, country, transcription_engine):
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audio, time_spoken = audio_queue.get()
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