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https://hdl.handle.net/10119/9580
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| Title: | Voice activity detection in a regularized reproducing kernel Hilbert space |
| Authors: | Lu, Xugang
Unoki, Masashi
Isotani, Ryosuke
Kawai, Hisashi
Nakamura, Satoshi |
| Keywords: | Statistical learning
reproducing kernel Hilbert space
voice activity detection |
| Issue Date: | 2010-09 |
| Publisher: | International Speech Communication Association |
| Magazine name: | Proceedings of INTERSPEECH 2010 |
| Start page: | 3086 |
| End page: | 3089 |
| Abstract: | Voice activity detection (VAD) is used to detect whether the acoustic signal belongs to speech or non-speech clusters based on the statistical distribution of the acoustic features. Traditional VAD algorithms are applied in a linear transformed space without any constraint relating to the special characteristics speech or noise. As a result, the VAD algorithms are not robust to noise interference. Considering that speech is a special type of acoustic signal that only occupies a small fraction of the whole acoustic space, we proposed a new speech feature extraction method by giving constraints on the processing space as a reproducing kernel Hilbert space (RKHS). In the RKHS, we regarded the speech estimation as a functional approximation problem, and estimated the approximation function via a regularized framework in the RKHS. Under this framework, we could incorporate the nonlinear mapping functions in the approximation implicitly via a kernel function. The approximation function could capture the nonlinear and high-order statistical regularities of the speech. Our VAD algorithm is designed on the basis of the power energy in this regularized RKHS. Compared with a baseline and G.729B VAD algorithms, experimental results showed the promising advantages of our proposed algorithm. |
| Rights: | Copyright (C) 2010 International Speech Communication Association. Xugang Lu, Masashi Unoki, Ryosuke Isotani, Hisashi Kawai, and Satoshi Nakamura, Proceedings of INTERSPEECH 2010, 2010, 3086-3089. |
| URI: | https://hdl.handle.net/10119/9580 |
| Material Type: | publisher |
| Appears in Collections: | b11-1. 会議発表論文・発表資料 (Conference Papers)
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| 15957-1.pdf | | 320Kb | Adobe PDF | View/Open |
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