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| # coding=utf-8 | |
| # Silence detection | |
| import logging | |
| import librosa | |
| import numpy as np | |
| class Step4: | |
| def __init__(self): | |
| self.log = logging.getLogger(self.__class__.__name__) | |
| self.log.setLevel(logging.INFO) | |
| def run(self, | |
| audio_path, | |
| silence_thresh=-50, | |
| duration_thresh=0.9): | |
| # self.log.info("Step4: Determine whether the audio is silent.") | |
| y, sr = librosa.load(audio_path, sr=None) | |
| energy = librosa.feature.rms(y=y)[0] | |
| energy_db = librosa.amplitude_to_db(energy) | |
| silent_ratio = np.sum(energy_db < silence_thresh) / len(energy_db) | |
| is_silent = silent_ratio > duration_thresh | |
| if is_silent: | |
| self.log.info(f"The audio after removing the voiceover ({audio_path}) is silent.") | |
| else: | |
| self.log.info(f"The audio after removing the voiceover ({audio_path}) is not silent.") | |
| self.log.info("Finish Step4 successfully.\n") | |
| return is_silent | |