王茂蓉, 周萍, 景新幸, 杨青. 基于Mel-TEO的带噪语音端点检测算法[J]. 微电子学与计算机, 2016, 33(4): 46-49.
引用本文: 王茂蓉, 周萍, 景新幸, 杨青. 基于Mel-TEO的带噪语音端点检测算法[J]. 微电子学与计算机, 2016, 33(4): 46-49.
WANG Mao-rong, ZHOU Ping, JING Xin-xing, YANG Qing. Voice Activity Detection Algorithm Based on Mel-TEO in Noisy Environment[J]. Microelectronics & Computer, 2016, 33(4): 46-49.
Citation: WANG Mao-rong, ZHOU Ping, JING Xin-xing, YANG Qing. Voice Activity Detection Algorithm Based on Mel-TEO in Noisy Environment[J]. Microelectronics & Computer, 2016, 33(4): 46-49.

基于Mel-TEO的带噪语音端点检测算法

Voice Activity Detection Algorithm Based on Mel-TEO in Noisy Environment

  • 摘要: 针对短时TEO能量算法抗噪性差的缺点, 提出了一种强噪声下的端点检测新算法.该算法在短时TEO能量端点检测的基础上, 增加Mel倒谱距离判断环节, 采用先粗判后精判的互补性两级判决机制.首先利用强抗噪性Mel倒谱距离进行端点粗判, 然后再利用体现语音信号时域特征与语音共振峰特性的短时TEO能量进行端点精判.实验表明, 在信噪比相对较低的环境下, 该改进算法与传统的双门限法和短时TEO能量相比, 在没有增加运算复杂度的同时提高了检测系统的准确度.

     

    Abstract: In order to solve the problem of the poor anti-noise performance, this paper proposes a new voice detection algorithm in noisy environment. On the basis of short-time TEO energy voice detection, increasing the judging section Mel Cepstral distance, we use two-stage decision mechanism with accurate judgment after rough judgment. First, we judge the voice endpoints preliminarily using Mel Cepstral distance which has a good anti-noise performance. Then, we judge the endpoints accurately using short-time TEO energy which reflects time-domain and voice formant characteristics of the speech signal. Experiments show that this algorithm has better capability in low SNR, compared with the traditional double thresholds and short-time TEO energy, without increasing the computational complexity and improving the accuracy of the detection system.

     

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