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Its critical problem is noise. Speech interfaces have become more familiar and more indispensable as smartphones and artificial intelligence (AI) speakers spread. Their critical problems are noise and multiple simultaneous speakers. Recently two technological advances have contributed to significantly improve the performance of speech interfaces and robot audition. Emerging deep learning technology has improved noise robustness of automatic speech recognition, whereas microphone array processing has improved the performance of preprocessing such as noise reduction. Herein, an overview and history of robot audition are provided together with introduction of an open\u2010source software for robot audition and its wide applications in the real world. Also, it is discussed how robot audition contributes to the development of computational auditory scene analysis, that is, understanding of real\u2010world auditory environments.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202000050","type":"journal-article","created":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T04:41:05Z","timestamp":1594183265000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Robot Audition and Computational Auditory Scene Analysis"],"prefix":"10.1002","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6134-4558","authenticated-orcid":false,"given":"Kazuhiro","family":"Nakadai","sequence":"first","affiliation":[{"name":"Research Division Honda Research Institute Japan Co., Ltd.  8-1 Honcho Wako Saitama 351\u20130188 Japan"},{"name":"Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology  2-12-1 Ookayama Meguro Tokyo 152\u20138552 Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroshi G.","family":"Okuno","sequence":"additional","affiliation":[{"name":"Graduate Program for Embodiment Informatics Waseda University  2-4-12 Lambdax Bldg. 301, O-kubo Shinjuku-ku Tokyo 169-0072 Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2020,7,8]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"K.Nakadai T.Lourens H. 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