91f948b0d6
* transcribe: return all language probabilities if requested If return_all_language_probs is True, TranscriptionInfo structure will have a list of tuples reflecting all language probabilities as returned by the model. * transcribe: fix docstring * transcribe: remove return_all_lang_probs parameter
77 lines
2.3 KiB
Python
77 lines
2.3 KiB
Python
import os
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from faster_whisper import WhisperModel, decode_audio
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def test_transcribe(jfk_path):
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model = WhisperModel("tiny")
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segments, info = model.transcribe(jfk_path, word_timestamps=True)
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assert info.all_language_probs is not None
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assert info.language == "en"
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assert info.language_probability > 0.9
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assert info.duration == 11
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# Get top language info from all results, which should match the
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# already existing metadata
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top_lang, top_lang_score = info.all_language_probs[0]
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assert info.language == top_lang
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assert abs(info.language_probability - top_lang_score) < 1e-16
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segments = list(segments)
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assert len(segments) == 1
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segment = segments[0]
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assert segment.text == (
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" And so my fellow Americans ask not what your country can do for you, "
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"ask what you can do for your country."
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)
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assert segment.text == "".join(word.word for word in segment.words)
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assert segment.start == segment.words[0].start
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assert segment.end == segment.words[-1].end
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def test_vad(jfk_path):
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model = WhisperModel("tiny")
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segments, info = model.transcribe(
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jfk_path,
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vad_filter=True,
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vad_parameters=dict(min_silence_duration_ms=500, speech_pad_ms=200),
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)
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segments = list(segments)
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assert len(segments) == 1
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segment = segments[0]
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assert segment.text == (
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" And so my fellow Americans ask not what your country can do for you, "
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"ask what you can do for your country."
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)
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assert 0 < segment.start < 1
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assert 10 < segment.end < 11
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assert info.vad_options.min_silence_duration_ms == 500
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assert info.vad_options.speech_pad_ms == 200
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def test_stereo_diarization(data_dir):
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model = WhisperModel("tiny")
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audio_path = os.path.join(data_dir, "stereo_diarization.wav")
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left, right = decode_audio(audio_path, split_stereo=True)
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segments, _ = model.transcribe(left)
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transcription = "".join(segment.text for segment in segments).strip()
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assert transcription == (
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"He began a confused complaint against the wizard, "
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"who had vanished behind the curtain on the left."
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)
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segments, _ = model.transcribe(right)
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transcription = "".join(segment.text for segment in segments).strip()
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assert transcription == "The horizon seems extremely distant."
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