Voice Activity Detection Based on Distance Entropy in Noisy Environment

Huan Zhao, Li-xia Zhao, Kai Zhao, Gangjin Wang
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引用次数: 7

Abstract

Voice Activity Detection is considered as a crucial part of the speech signal processing. In order to improve the accuracy of Voice Activity Detection under the high-noisy environment, an algorithm named distance entropy is proposed. The algorithm firstly enhances speech with short time spectral amplitude, and then utilizes the robustness of cepstral distance and spectral entropy. The experimental results show that this method performs well on anti-noise, and is more accurate to detect the endpoint in low SNR environment.
噪声环境下基于距离熵的语音活动检测
语音活动检测是语音信号处理的重要组成部分。为了提高高噪声环境下语音活动检测的准确性,提出了一种距离熵算法。该算法首先利用短时谱幅增强语音,然后利用倒谱距离和谱熵的鲁棒性。实验结果表明,该方法具有良好的抗噪性能,在低信噪比环境下能够更准确地检测到端点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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