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