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

来源：

IEEE TRANSACTIONS ON CONSUMER ELECTRONICS | 2010年 / 56卷 / 02期

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

页码：764 / 769

页数：6

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