オオイシ　クニオ   大石　邦夫    所属   コンピュータサイエンス学部 コンピュータサイエンス学科    職種   教授
言語種別	英語
発行・発表の年月	2019/09
形態種別	学術論文
査読	査読あり
標題	Determined and overdetermined convolutive blind source extractions by approximate joint diagonalization
執筆形態	共著
掲載誌名	Acoustical Science and Technology
巻・号・頁	40(5),pp.302-312
総ページ数	11
著者・共著者	Shinya Saito, Kunio Oishi, and Toshihiro Furukawa
概要	Blind extraction of convolutive speech mixtures can be achieved by the approximate joint diagonalization (AJD) approach. In this paper, we present a least-squares AJD (LS-AJD) algorithm, called fast diagonalization, implemented by minimizing the direct and indirect LS criteria (FDMDI) algorithm. The proposed approach is based on an alternate minimization of the indirect and direct least-squares criteria to the diagonal matrices in the first phase and to the mixing matrix in the second phase, respectively. In our proposed approach, the constrained LS-AJD estimation problem is solved by the method of Lagrange multipliers; moreover, the mixing matrix is estimated by a non-iterative method without a nested loop in the second phase. The simulation result demonstrates that overdetermined FDMDI blind source extraction (BSE) provides more effective extracted signals than determined FDMDI BSE in an actual acoustic environment.
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