.png){kind=icon}
返回
Robust Speech Recognition Using Improved Vector Taylor Series Algorithm for Embedded Systems
.png){kind=icon}
PRE
AI
DOI：10.1109/TCE.2010.5505999.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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).
Keyword:
Robust speech recognition
vector Taylor series
feature compensation
hidden Markov model
期刊
IF:
10.9
论文数:
5.3K
被引数:
6.8K
机构
引用论文
.png){kind=icon}
分享收藏
查看更多内容