Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
ZennyKenny
commited on
handle audio input
Browse files
app.py
CHANGED
@@ -19,20 +19,25 @@ def transcribe_long_audio(audio_input, transcriber, chunk_duration=30):
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try:
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if isinstance(audio_input, tuple): # Recorded audio
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audio_data, sr = audio_input # Unpack raw audio data and sample rate
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elif isinstance(audio_input, str): # Uploaded file path
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-
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else:
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raise ValueError("Unsupported audio input format.")
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#
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chunks = split_audio(audio_data, sr, chunk_duration)
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transcriptions = []
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for i, chunk in enumerate(chunks):
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-
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sf.write(
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transcription = transcriber(
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transcriptions.append(transcription)
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os.remove(
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return " ".join(transcriptions)
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except Exception as e:
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return f"Error processing audio: {e}"
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@@ -62,27 +67,16 @@ def main():
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# Enable recording or file upload
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audio_input = gr.Audio(type="numpy", label="Record or Upload Audio")
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process_button = gr.Button("Process Audio")
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stop_button = gr.Button("Stop Recording") # Add Stop Button
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with gr.Column():
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transcription_output = gr.Textbox(label="Full Transcription", lines=10)
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summary_output = gr.Textbox(label="Summary", lines=5)
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def stop_microphone():
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"""Dummy function to simulate stopping the microphone."""
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return "Recording stopped."
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process_button.click(
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process_audio,
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inputs=[audio_input],
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outputs=[transcription_output, summary_output]
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)
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stop_button.click(
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stop_microphone,
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inputs=[],
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outputs=[],
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)
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interface.launch(share=True)
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if __name__ == "__main__":
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try:
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if isinstance(audio_input, tuple): # Recorded audio
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audio_data, sr = audio_input # Unpack raw audio data and sample rate
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temp_path = "recorded_audio.wav"
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sf.write(temp_path, audio_data, sr) # Save recorded audio as a temporary file
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elif isinstance(audio_input, str): # Uploaded file path
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temp_path = audio_input # Use the file path directly
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else:
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raise ValueError("Unsupported audio input format.")
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# Process the audio file (recorded or uploaded)
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audio_data, sr = librosa.load(temp_path, sr=None)
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chunks = split_audio(audio_data, sr, chunk_duration)
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transcriptions = []
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for i, chunk in enumerate(chunks):
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chunk_path = f"temp_chunk_{i}.wav"
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sf.write(chunk_path, chunk, sr) # Save chunk as WAV
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transcription = transcriber(chunk_path)["text"]
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transcriptions.append(transcription)
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os.remove(chunk_path) # Cleanup temp files
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if temp_path == "recorded_audio.wav":
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os.remove(temp_path) # Remove the temporary recorded audio file
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return " ".join(transcriptions)
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except Exception as e:
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return f"Error processing audio: {e}"
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# Enable recording or file upload
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audio_input = gr.Audio(type="numpy", label="Record or Upload Audio")
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process_button = gr.Button("Process Audio")
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with gr.Column():
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transcription_output = gr.Textbox(label="Full Transcription", lines=10)
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summary_output = gr.Textbox(label="Summary", lines=5)
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process_button.click(
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process_audio,
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inputs=[audio_input],
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outputs=[transcription_output, summary_output]
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)
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interface.launch(share=True)
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if __name__ == "__main__":
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