基于盲源分离和噪声抑制的语音信号识别

Speech Signal Recognition Based on Blind Source Separation and Noise Suppression

摘要:

本文提出了一种用于普适语音环境下的个性化语音命令自动识别系统的信号恢复算法,该算法能够从多个发声者中分离混合语音源,通过跟踪语音功率谱的较高幅度部分和自适应地抑制噪声来检测发声者。设计并实现了一种处理多发声者任务的自动语音识别(ASR)。使用语音数据库NOIZEUS进行了评价测试,实验结果表明,所提出的盲源分离和噪声抑制方法不需要任何额外的计算过程,有效地减少了计算负担。

Abstract:

This paper presents a signal recovery algorithm for the personalized speech command automatic recognition system in the ubiquitous voice environment. This algorithm can separate the mixed speech source from the multiple voice transmitter, and detect the speaker by tracking the high amplitude part of the speech power spectrum and suppressing the noise adaptively. An automatic speech recognition (ASR) is designed and implemented to deal with multiple vocalizations. The experimental results show that the proposed method of source separation and noise suppression does not require any additional computation process and effectively reduces the calculation burden, using the speech database NOIZEUS.