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

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%.