Robust Speech Recognition Using Improved Vector Taylor Series Algorithm for Embedded Systems

被引:3
|
作者
Lue, Yong [1 ]
Wu, Haiyang [1 ]
Wu, Zhenyang [1 ]
机构
[1] Southeast Univ, Sch Informat Sci & Engn, Nanjing, Peoples R China
基金
中国国家自然科学基金;
关键词
Robust speech recognition; vector Taylor series; feature compensation; hidden Markov model; ENVIRONMENTS;
D O I
10.1109/TCE.2010.5505999
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes a novel robust speech recognition technique using improved vector Taylor series (VTS) algorithm for embedded systems. It uses a hidden Markov model (HMM) to replace the Gaussian mixture model (GMM) for estimating the clean speech feature, and gives the closed-form solutions of the noise parameters including the mean and variance at each expectation-maximization (EM) iteration. The experimental results show that the proposed algorithm makes a good balance between the computational complexity and recognition accuracy, and thus is more useful for embedded systems(1).
引用
收藏
页码:764 / 769
页数:6
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