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KMID : 1022420100020030141
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Phonetics and Speech Sciences
2010 Volume.2 No. 3 p.141 ~ p.148
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Statistical Model-Based Voice Activity Detection Using Spatial Cues for Dual-Channel Noisy Speech Recognition
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Shin Min-Hwa
Park Ji-Hun
Kim Hong-Kook
Lee Seong-Ro
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Abstract
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In this paper, voice activity detection (VAD) for dual-channel noisy speech recognition is proposed in which spatial cues are employed. In the proposed method, a probability model for speech presence/absence is constructed using spatial cues obtained from dual-channel input signal, and a speech activity interval is detected through this probability model. In particular, spatial cues are composed of interaural time differences and interaural level differences of dual-channel speech signals, and the probability model for speech presence/absence is based on a Gaussian kernel density. In order to evaluate the performance of the proposed VAD method, speech recognition is performed for speech segments that only include speech intervals detected by the proposed VAD method. The performance of the proposed method is compared with those of several methods such as an SNR-based method, a direction of arrival (DOA) based method, and a phase vector based method. It is shown from the speech recognition experiments that the proposed method outperforms conventional methods by providing relative word error rates reductions of 11.68%, 41.92%, and 10.15% compared with SNR-based, DOA-based, and phase vector based method, respectively.
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KEYWORD
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voice activity detection (VAD), dual-channel speech, speech recognition, spatial cues
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