A Comparative Study of Spatial Speech Separation Techniques to Improve Speech Recognition

被引：0
|
作者：
Zhou, Xinhui [1 ]
Kwan, Chiman [1 ]
Ayhan, Bulent [1 ]
Kim, Chanwoo [2 ]
Kumar, K. [2 ]
Stern, Richard [2 ]
机构：
[1] Signal Proc Inc, Rockville, MD 20850 USA
[2] Carnegie Mellon Univ, Pittsburgh, PA USA
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2018 | 2018年 / 10878卷
基金：
美国国家科学基金会;
关键词：
Speech recognition; Spatial speech separation; Reverberant;
D O I：
10.1007/978-3-319-92537-0_57
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Robust speech recognition in noisy and reverberant conditions is an important research area in recent years. Here we present a comparative study of several spatial speech separation methods. The main performance metric is word error rate (WER) under different signal-to-noise ratio (SNR) and reverberant conditions. Extensive simulations showed that one technique known as polyaural processing stood out as the best one.
引用
收藏
页码：494 / 502
页数：9
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