An Improvement in Audio-Visual Voice Activity Detection for Automatic Speech Recognition

被引：0
|
作者：
Yoshida, Takami [1 ]
Nakadai, Kazuhiro [1 ,2 ]
Okuno, Hiroshi G. [3 ]
机构：
[1] Tokyo Inst Technol, Grad Sch Informat Sci & Engn, Tokyo 152, Japan
[2] Honda Res Inst Japan Co Ltd, Saitama, Japan
[3] Kyoto Univ, Grad Sch Informat, Kyoto, Japan
来源：
TRENDS IN APPLIED INTELLIGENT SYSTEMS, PT I, PROCEEDINGS | 2010年 / 6096卷
关键词：
Audio-Visual integration; Voice Activity Detection; Speech Recognition;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Noise-robust Automatic Speech Recognition (ASR) is essential for robots Much are expected to communicate with humans in a daily environment In such an environment; Voice Activity Detection (VAD) Strongly affects the performance of ASR, because dime are many acoustically and visually noises In this paper; we improved Audio-Visual VAD for out two-layered audio visual integration framework for ASR, by using hangover processing based on erosion and dilation We implemented proposed method to our audio-visual speech if:cognition system for robot, Empirical results show v. the effectiveness of our pi posed method in terms of VAD
引用
收藏
页码：51 / +
页数：3
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