Efficient blind dereverberation framework for automatic speech recognition
Efficient blind dereverberation framework for automatic speech recognition
复制标题
用于自动语音识别的高效盲去混响框架
DOI：
10.21437/interspeech.2005-269
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发表时间：
2005
影响因子：
--
通讯作者：
M. Miyoshi
中科院分区：
文献类型：
--
作者：
K. Kinoshita;T. Nakatani;M. Miyoshi
远距离麦克风捕获的语音信号通常会受到混响的影响，这严重降低了自动语音识别(ASR)的性能。本文利用语音与混响之间的关系，提出了一种新颖实用的单通道去混响方案。由该方法得到的去混响fi能够有效地抑制延迟响应，而延迟响应是ASR性能下降的主要原因。与传统方法相比，该算法能够以更合理的计算复杂度实现有效的去混响。实验结果表明，即使在严重混响的环境中，ASR性能也有显著的改善
A speech signal captured by a distant microphone is generally smeared by reverberation, which severely degrades Automatic Speech Recognition (ASR) performance. In this paper, we propose a novel and practical single channel dereverberation scheme, which utilizes the relationship between speech and re-verberation. A dereverberation filter derived by the proposed method is capable of efficiently suppressing late reflections, which constitute a major cause of ASR performance degradation. The proposed algorithm can achieve effective derever-beration with a more reasonable computational complexity than conventional methods. Experimental results reveal a substantial improvement in ASR performance even in severely reverberant environments
影响因子：
4.3
作者：
LEGGETTER, CJ;WOODLAND, PC
通讯作者：
WOODLAND, PC