Study of talker localization based on subband CSP analysis in real noisy environments

Summary form only given. It is very important to capture distant-talking speech with high quality for hands-free speech acquisition systems. Microphone array steering is an ideal candidate for capturing distant-talking speech with high quality. However, it requires localizing a target talker before capturing distant-talking speech. Conventional talker localization methods cannot localize a target talker accurately in higher noisy environments. To deal with this problem, in this paper, we propose a new talker localization method based on subband CSP analysis with weighting of an average speech spectrum. It consists of subband analysis with equal bandwidth on mel-frequency and analysis weight coefficients based on an average speech spectrum, which are trained with a speech database, in advance. As a result of evaluation experiments in a real room, we confirmed that the proposed method could provide better talker localization performance than the conventional methods.