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from speechbox import PunctuationRestorer |
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import librosa |
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import subprocess |
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import gradio as gr |
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restorer = PunctuationRestorer.from_pretrained("openai/whisper-tiny.en") |
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def convert_to_wav(path): |
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if path[-3:] != 'wav': |
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new_path = '.'.join(path.split('.')[:-1]) + '.wav' |
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try: |
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subprocess.call(['ffmpeg', '-i', path, new_path, '-y']) |
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except: |
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return path, 'Error: Could not convert file to .wav' |
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path = new_path |
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return path, None |
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def restore(audio, original_transcript): |
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path, error = convert_to_wav(audio) |
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print(error) |
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data, samplerate = librosa.load(path, sr=16_000) |
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text, log_probs = restorer(data, original_transcript, samplerate, num_beams=1) |
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return text, log_probs |
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gr.Interface( |
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title='Punctuation Restorer', |
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fn=restore, |
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inputs=[ |
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gr.inputs.Audio(source="upload", type="filepath"), |
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gr.inputs.Textbox(default="", label="normalized text") |
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], |
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outputs=[ |
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gr.outputs.Textbox(label='Restored text'), |
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gr.Number(label='Log probability') |
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], |
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examples=[ |
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["./common_voice_en_18301577.mp3", "do not cross the yellow light"], |
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["./sample1.flac", "going along slushy country roads and speaking to damp audiences in draughty school rooms day after day for a fortnight he'll have to put in an appearance at some place of worship on sunday morning and he can come to us immediately afterwards"], |
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["./sample2.flac", "before he had time to answer a much encumbered vera burst into the room with the question i say can i leave these here these were a small black pig and a lusty specimen of black red game cock"], |
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] |
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).launch() |
