NDLI: Speaker verification method using bone-conduction and air-conduction speech

Content Provider	IEEE Xplore Digital Library
Author	Tsuge, S. Koizumi, D. Fukumi, M. Kuroiwa, S.
Copyright Year	2009
Description	Author affiliation: Chiba University, Japan (Kuroiwa, S.) \|\| The University of Tokushima, Japan (Tsuge, S.; Koizumi, D.; Fukumi, M.)
Abstract	Recently, some new sensors, such as bone-conductive microphones, throat microphones, and non-audible murmur (NAM) microphones, besides conventional condenser microphones have been developed for collecting speech data. Accordingly, some researchers began to study speaker and speech recognition using speech data collected by these new sensors. We focus on bone-conduction speech data collected by the bone-conductive microphone. In this paper, we first investigate speaker verification performances of bone-conduction speech. In addition, we propose a method of using bone-conduction speech and air-conduction together for the speaker verification. The proposed method integrates the similarity calculated by air-conduction speech model and similarity calculated by bone-conduction speech model. Using 99 female speakers' speech data, we conducted speaker verification experiments. Experimental results show that the speaker verification performance of bone-conduction is lower than that of air-conduction speech. However, the proposed method can improve the speaker verification performance of bone- and air-conduction speech. Actually, the proposed method can reduce the equal error rate of air-conduction speech by 16.0% and the equal error rate of bone-conduction speech by 71.7%.
Starting Page	449
Ending Page	452
File Size	152817
Page Count	4
File Format	PDF
ISBN	9781424450152
DOI	10.1109/ISPACS.2009.5383806
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-01-07
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Microphones Speech recognition Intelligent sensors Speech processing Error analysis Personal digital assistants Home appliances Speech enhancement Signal processing Sensor systems Combination air- and bone-conduction speech Speaker verification Bone-conduction speech Air-conduction speech
Content Type	Text
Resource Type	Article

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