检索结果-内蒙古大学图书馆

Noise adaptive speech recognition based on sequential noise parameter estimation

SPEECH COMMUNICATION 2004年第1期42卷 5-23页

作者： Yao, KS Paliwal, KK Nakamura, S ATR Spoken Language Translat Res Labs Kyoto Japan Griffith Univ Sch Microelect Engn Brisbane Qld Australia

In this paper, a noise adaptive speech recognition approach is proposed for recognizing speech which is corrupted by additive non-stationary background noise. The approach sequentially estimates noise parameters, through which a nonlinear parametric function adapts mean vectors of acoustic models. In the estimation process, posterior probability of state sequence given observation sequence and the previously estimated noise parameter sequence is approximated by the normalized joint likelihood of active partial paths and observation sequence given the previously estimated noise parameter sequence. The Viterbi process provides the normalized joint-likelihood. The acoustic models are not required to be trained from clean speech and they can be trained from noisy speech. The approach can be applied to perform continuous speech recognition in presence of non-stationary noise. Experiments conducted on speech contaminated by simulated and real non-stationary noise show that when acoustic models are trained from clean speech, the noise adaptive speech recognition system provides improvements in word accuracy as compared to the normal noise compensation system (which assumes the noise to be stationary) in slowly time-varying noise. When the acoustic models are trained from noisy speech, the noise adaptive speech recognition system is found to be helpful to get improved performance in slowly time-varying noise over a system employing multi-conditional training. (C) 2003 Elsevier B.V. All rights reserved.

关键词： noisy speech recognition non-stationary noise expectation maximization algorithm kullback proximal algorithm

来源：评论

学校读者我要写书评

暂无评论

Noise adaptive speech recognition based on sequential noise parameter estimation

Noise adaptive speech recognition based on sequential noise ...

引用

Workshop on Adaptation Methods for Speech Recognition

作者： Yao, KS Paliwal, KK Nakamura, S ATR Spoken Language Translat Res Labs Kyoto Japan Griffith Univ Sch Microelect Engn Brisbane Qld Australia

关键词： noisy speech recognition non-stationary noise expectation maximization algorithm kullback proximal algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：