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import gradio as gr |
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from transformers import pipeline |
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import numpy as np |
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import librosa |
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import pandas as pd |
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MODEL_NAME = "openai/whisper-large-v3" |
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BATCH_SIZE = 8 |
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pipe = pipeline( |
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task="automatic-speech-recognition", |
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model=MODEL_NAME, |
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chunk_length_s=30, |
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) |
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def format_output_to_list(data): |
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formatted_list = "\n".join([f"{item['timestamp'][0]}s - {item['timestamp'][1]}s \t : {item['text']}" for item in data]) |
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return formatted_list |
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def transcribe(inputs, task): |
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if inputs is None: |
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raise gr.Error("No audio file submitted! Please upload or record an audio file before submitting your request.") |
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output = pipe(inputs, batch_size=BATCH_SIZE, return_timestamps="word", generate_kwargs={"task": task}) |
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text = output['text'] |
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timestamps = format_output_to_list(output['chunks']) |
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return [text, timestamps] |
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examples = [ |
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["arabic_english_audios/audios/arabic_audio_1.wav"], |
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["arabic_english_audios/audios/arabic_audio_2.wav"], |
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["arabic_english_audios/audios/arabic_audio_3.wav"], |
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["arabic_english_audios/audios/arabic_audio_4.wav"], |
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["arabic_english_audios/audios/arabic_hate_audio_1.mp3"], |
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["arabic_english_audios/audios/arabic_hate_audio_2.mp3"], |
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["arabic_english_audios/audios/arabic_hate_audio_3.mp3"], |
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["arabic_english_audios/audios/english_audio_1.wav"], |
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["arabic_english_audios/audios/english_audio_2.mp3"], |
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["arabic_english_audios/audios/english_audio_3.mp3"], |
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["arabic_english_audios/audios/english_audio_4.mp3"], |
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["arabic_english_audios/audios/english_audio_5.mp3"], |
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["arabic_english_audios/audios/english_audio_6.wav"] |
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] |
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with gr.Blocks(theme=gr.themes.Default()) as demo: |
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gr.HTML("<h1 style='text-align: center;'>Transcribe Audio with Timestamps using whisper-large-v3</h1>") |
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gr.Markdown("") |
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with gr.Row(): |
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with gr.Column(): |
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audio_input = gr.Audio(sources=["upload", 'microphone'], type="filepath", label="Audio file") |
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task = gr.Radio(["transcribe", "translate"], label="Task") |
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with gr.Row(): |
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clear_button = gr.ClearButton(value="Clear") |
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submit_button = gr.Button("Submit", variant="primary", ) |
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with gr.Column(): |
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transcript_output = gr.Text(label="Transcript") |
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timestamp_output = gr.Text(label="Timestamp") |
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examples = gr.Examples(examples, inputs=audio_input, outputs=[transcript_output, timestamp_output], fn=transcribe, examples_per_page=20) |
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submit_button.click(fn=transcribe, inputs=audio_input, outputs=[transcript_output, timestamp_output]) |
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clear_button.add([audio_input, transcript_output, timestamp_output]) |
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if __name__ == "__main__": |
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demo.launch() |
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