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import whisper |
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from .compute_vps_score import compute_vps_score |
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def main(): |
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audio_path = r"D:\Intern\shankh\audio_samples\obama_short.wav" |
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model_size = "base" |
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print(f"Loading Whisper model: {model_size}") |
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whisper_model = whisper.load_model(model_size) |
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print(f"Analyzing audio: {audio_path}") |
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try: |
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vps_result = compute_vps_score(audio_path, whisper_model) |
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print("\n--- Voice Pacing Score (VPS) ---") |
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print(f"VPS Score: {vps_result['VPS']:.2f}") |
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print(f" - SRS (Speech Rate Stability): {vps_result['SRS']:.2f}") |
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print(f" - PAS (Pause Appropriateness): {vps_result['PAS']:.2f}") |
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print(f" - NPP: {vps_result['NPP']:.2f}") |
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print(f" - AFW: {vps_result['AFW']:.2f}") |
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print(f" - RCS (Rhythm Consistency): {vps_result['RCS']:.2f}") |
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print(f" - STR: {vps_result['STR']:.2f}") |
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print(f" - STW: {vps_result['STW']:.2f}") |
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print("\nTranscript:") |
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print(vps_result["transcript"]) |
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except Exception as e: |
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print(f"[Error] {e}") |
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if __name__ == "__main__": |
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main() |
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