Spaces:
Sleeping
Sleeping
Do not parallelize period vad
Browse files- src/vad.py +10 -0
- src/vadParallel.py +1 -1
src/vad.py
CHANGED
@@ -77,6 +77,12 @@ class AbstractTranscription(ABC):
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def get_audio_segment(self, str, start_time: str = None, duration: str = None):
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return load_audio(str, self.sampling_rate, start_time, duration)
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@abstractmethod
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def get_transcribe_timestamps(self, audio: str, config: TranscriptionConfig, start_time: float, end_time: float):
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"""
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@@ -462,6 +468,10 @@ class VadPeriodicTranscription(AbstractTranscription):
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def __init__(self, sampling_rate: int = 16000):
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super().__init__(sampling_rate=sampling_rate)
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def get_transcribe_timestamps(self, audio: str, config: PeriodicTranscriptionConfig, start_time: float, end_time: float):
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result = []
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def get_audio_segment(self, str, start_time: str = None, duration: str = None):
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return load_audio(str, self.sampling_rate, start_time, duration)
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def is_transcribe_timestamps_fast(self):
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"""
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Determine if get_transcribe_timestamps is fast enough to not need parallelization.
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"""
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return False
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@abstractmethod
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def get_transcribe_timestamps(self, audio: str, config: TranscriptionConfig, start_time: float, end_time: float):
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"""
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def __init__(self, sampling_rate: int = 16000):
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super().__init__(sampling_rate=sampling_rate)
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def is_transcribe_timestamps_fast(self):
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# This is a very fast VAD - no need to parallelize it
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return True
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def get_transcribe_timestamps(self, audio: str, config: PeriodicTranscriptionConfig, start_time: float, end_time: float):
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result = []
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src/vadParallel.py
CHANGED
@@ -90,7 +90,7 @@ class ParallelTranscription(AbstractTranscription):
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total_duration = get_audio_duration(audio)
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# First, get the timestamps for the original audio
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if (cpu_device_count > 1):
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merged = self._get_merged_timestamps_parallel(transcription, audio, config, total_duration, cpu_device_count, cpu_parallel_context)
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else:
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timestamp_segments = transcription.get_transcribe_timestamps(audio, config, 0, total_duration)
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total_duration = get_audio_duration(audio)
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# First, get the timestamps for the original audio
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if (cpu_device_count > 1 and not transcription.is_transcribe_timestamps_fast()):
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merged = self._get_merged_timestamps_parallel(transcription, audio, config, total_duration, cpu_device_count, cpu_parallel_context)
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else:
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timestamp_segments = transcription.get_transcribe_timestamps(audio, config, 0, total_duration)
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