Reducing Computational Complexity of Multichannel Nonnegative Matrix Factorization Using Initial Value Setting for Speech Recognition - researchr publication authors

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Taiki Izumi, Ryo Aihara, Toshiyuki Hanazawa, Yohei Okato, Takanobu Uramoto, Shingo Uenohara, Ken'ichi Furuya. Reducing Computational Complexity of Multichannel Nonnegative Matrix Factorization Using Initial Value Setting for Speech Recognition. In Leonard Barolli, Nadeem Javaid, Makoto Ikeda, Makoto Takizawa, editors, Complex, Intelligent, and Software Intensive Systems - Proceedings of the 12th International Conference on Complex, Intelligent, and Software Intensive Systems, CISIS-2018, Matsue, Japan, 4-6 July 2018. Volume 772 of Advances in Intelligent Systems and Computing, pages 893-900, Springer, 2018. [doi]

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