著者

久木原 健介 和久屋 寛 伊藤 秀昭 福本 尚生 古川 達也

出版者

一般社団法人 産業応用工学会

雑誌

産業応用工学会全国大会講演論文集 2013 (ISSN:2424211X)

巻号頁・発行日

pp.18-19, 2013 (Released:2018-04-10)

参考文献数

5

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Independent component analysis (ICA) is a signal separation technique inspired by the famous psychological phenomenon called cocktail party effect. Various kinds of its applications have been undertaken by a lot of researchers so far, and an alternative method based on a layered neural network with structural pruning was tried in the preceding studies. However, how to develop such a signal separation matrix was the center of attention, so how to apply it after training was not discussed a lot. Then, from the viewpoint of adaptability to untrained signals, some computer simulations are carried out in this study. As a result, it is found experimentaly that a vocal signal separation task with the developed separation matrix is accomplished successfully as we have intended in advance.