NDLI: Wake-up-word detection for robots using spatial eigenspace consistency and resonant curve similarity

Content Provider	IEEE Xplore Digital Library
Author	Jwu-Sheng Hu Ming-Tang Lee Ting-Chao Wang
Copyright Year	2011
Description	Author affiliation: National Chiao Tung University, Hshinchu, Taiwan, ROC (Jwu-Sheng Hu; Ming-Tang Lee; Ting-Chao Wang)
Abstract	In this paper, we propose a method to detect the wake-up-word (WUW) using microphone array for human-robot interaction. The consistency of the spatial eigenspaces formed by the speech source at different frequencies and the resonant curve similarity of the WUW are used as the features for detection. These features are processed and detected separately and the result is determined by cascading individual outcome using Bayes risk detector. This proposed method can keep a high recognition rate under very low signal-to-noise ratio (SNR) conditions. In addition, this method can estimate the direction of arrivals of the sound source, and the proposed architecture is easy to expand by adding detectors with other features in the cascaded manner to further improve the recognition rate.
Starting Page	3901
Ending Page	3906
File Size	442301
Page Count	6
File Format	PDF
ISBN	9781612843865
ISSN	10504729
e-ISBN	9781612843858
DOI	10.1109/ICRA.2011.5979722
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech Signal to noise ratio Detectors Feature extraction Multiple signal classification Arrays Testing
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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