Merge pull request #398 from AlexStansfield/feature/faster-whisper-1.2.0
feat: update to support faster whisper 1.2.0
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@@ -1,4 +1,4 @@
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faster-whisper==1.1.0
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faster-whisper==1.2.0
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websockets
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websockets
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onnxruntime==1.17.0
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onnxruntime==1.17.0
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numba
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numba
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@@ -76,7 +76,7 @@ class ServeClientFasterWhisper(ServeClientBase):
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self.language = "en" if self.model_size_or_path.endswith("en") else language
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self.language = "en" if self.model_size_or_path.endswith("en") else language
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self.task = task
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self.task = task
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self.initial_prompt = initial_prompt
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self.initial_prompt = initial_prompt
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self.vad_parameters = vad_parameters or {"onset": 0.5}
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self.vad_parameters = vad_parameters or {"threshold": 0.5}
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device = "cuda" if torch.cuda.is_available() else "cpu"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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if device == "cuda":
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if device == "cuda":
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@@ -27,7 +27,6 @@ from faster_whisper.vad import (
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VadOptions,
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VadOptions,
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collect_chunks,
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collect_chunks,
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get_speech_timestamps,
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get_speech_timestamps,
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merge_segments,
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)
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)
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@@ -407,8 +406,7 @@ class BatchedInferencePipeline:
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**vad_parameters, max_speech_duration_s=chunk_length
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**vad_parameters, max_speech_duration_s=chunk_length
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)
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)
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active_segments = get_speech_timestamps(audio, vad_parameters)
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clip_timestamps = get_speech_timestamps(audio, vad_parameters)
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clip_timestamps = merge_segments(active_segments, vad_parameters)
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# run the audio if it is less than 30 sec even without clip_timestamps
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# run the audio if it is less than 30 sec even without clip_timestamps
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elif duration < chunk_length:
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elif duration < chunk_length:
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clip_timestamps = [{"start": 0, "end": audio.shape[0]}]
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clip_timestamps = [{"start": 0, "end": audio.shape[0]}]
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