| 摘要 |
PROBLEM TO BE SOLVED: To provide a sound source separation and localization method, capable of improving sound source localization/sound source separation performance, even when observed feature amounts are not clearly clustered and overlap each other due to reverberation and background noise. SOLUTION: A new algorithm in which expectation maximization (EM) algorithm is applied for a blind sound source separation (BSS) problem, is proposed. Concretely, based on sparse nature of a sound source signal, a sound source direction which gives a maximum likelihood and a contribution rate of each sound source to each time frequency component, are estimated by the EM algorithm, by setting an index of the sound source which contributes to each time frequency component as an hidden variable, on the basis of an observation model that only one sound source contributes to each time frequency component. As a result, separation and localization of the sound source can be achieved, even when reverberation time is long. COPYRIGHT: (C)2008,JPO&INPIT
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