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from speechbox import PunctuationRestorer |
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import soundfile as sf |
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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 = sf.read(path) |
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text, probs = restorer(data, original_transcript, samplerate, num_beams=1) |
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return text, 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.Text(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.outputs.Number(label='Log prob') |
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] |
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).launch() |
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