Update benchmark.sh
Browse files- benchmark.sh +2 -15
benchmark.sh
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@@ -5,18 +5,5 @@ ffmpeg -i kotoba-whisper-eval/audio/long_interview_1.mp3 -ar 16000 -ac 1 -c:a pc
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ffmpeg -i kotoba-whisper-eval/audio/manzai1.mp3 -ar 16000 -ac 1 -c:a pcm_s16le kotoba-whisper-eval/audio/manzai1.wav
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ffmpeg -i kotoba-whisper-eval/audio/manzai2.mp3 -ar 16000 -ac 1 -c:a pcm_s16le kotoba-whisper-eval/audio/manzai2.wav
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ffmpeg -i kotoba-whisper-eval/audio/manzai3.mp3 -ar 16000 -ac 1 -c:a pcm_s16le kotoba-whisper-eval/audio/manzai3.wav
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#
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python
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SECONDS=0
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python -c 'from faster_whisper import WhisperModel; model = WhisperModel("kotoba-tech/kotoba-whisper-v1.0-faster"); print(["[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text) for segment in model.transcribe("kotoba-whisper-eval/audio/long_interview_1.wav", language="ja", chunk_length=15, condition_on_previous_text=False)[0]])'
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TIME_INTERVIEW=$SECONDS
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SECONDS=0
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python -c 'from faster_whisper import WhisperModel; model = WhisperModel("kotoba-tech/kotoba-whisper-v1.0-faster"); print(["[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text) for segment in model.transcribe("kotoba-whisper-eval/audio/manzai1.wav", language="ja", chunk_length=15, condition_on_previous_text=False)[0]])'
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TIME_MANZAI1=$SECONDS
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SECONDS=0
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python -c 'from faster_whisper import WhisperModel; model = WhisperModel("kotoba-tech/kotoba-whisper-v1.0-faster"); print(["[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text) for segment in model.transcribe("kotoba-whisper-eval/audio/manzai2.wav", language="ja", chunk_length=15, condition_on_previous_text=False)[0]])'
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TIME_MANZAI2=$SECONDS
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SECONDS=0
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python -c 'from faster_whisper import WhisperModel; model = WhisperModel("kotoba-tech/kotoba-whisper-v1.0-faster"); print(["[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text) for segment in model.transcribe("kotoba-whisper-eval/audio/manzai3.wav", language="ja", chunk_length=15, condition_on_previous_text=False)[0]])'
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TIME_MANZAI3=$SECONDS
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ffmpeg -i kotoba-whisper-eval/audio/manzai1.mp3 -ar 16000 -ac 1 -c:a pcm_s16le kotoba-whisper-eval/audio/manzai1.wav
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ffmpeg -i kotoba-whisper-eval/audio/manzai2.mp3 -ar 16000 -ac 1 -c:a pcm_s16le kotoba-whisper-eval/audio/manzai2.wav
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ffmpeg -i kotoba-whisper-eval/audio/manzai3.mp3 -ar 16000 -ac 1 -c:a pcm_s16le kotoba-whisper-eval/audio/manzai3.wav
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# run the benchmark
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python benchmark.py
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