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import gradio as gr |
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import librosa |
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import pydub |
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import profanity_check |
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import openai |
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def clean_song(file_path): |
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audio_file = librosa.load(file_path) |
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acapella = librosa.effects.trim(audio_file, top_db=60) |
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transcript = openai.engine("text-davinci-002").generate( |
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text="What is the acapella of this song?", |
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prompt="Listen to this audio file: " + acapella.to_wav().hex(), |
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temperature=0.7, |
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max_tokens=200, |
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) |
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profane_words = profanity_check.get_profanity(transcript) |
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timestamps = [ |
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(m.start(), m.end()) for m in profanity_check.match_all(transcript) |
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] |
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audio = pydub.AudioSegment.from_wav(file_path) |
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for start, end in timestamps: |
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audio[start:end].set_volume(0) |
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audio.export("clean_song.wav", format="wav") |
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return "Clean audio file saved as clean_song.wav" |
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gr.Interface(clean_song, inputs="file", outputs="text").launch() |
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