{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,9,13]],"date-time":"2023-09-13T21:17:24Z","timestamp":1694639844724},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2010,3,1]],"date-time":"2010-03-01T00:00:00Z","timestamp":1267401600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This paper describes an improvement in automatic speech recognition (ASR) for robot audition by introducing Missing Feature Theory (MFT) based on soft missing feature masks (MFM) to realize natural human-robot interaction. In an everyday environment, a robot\u2019s microphones capture various sounds besides the user\u2019s utterances. Although sound-source separation is an effective way to enhance the user\u2019s utterances, it inevitably produces errors due to reflection and reverberation. MFT is able to cope with these errors. First, MFMs are generated based on the reliability of time-frequency components. Then ASR weighs the time-frequency components according to the MFMs. We propose a new method to automatically generate soft MFMs, consisting of continuous values from 0 to 1 based on a sigmoid function. The proposed MFM generation was implemented for HRP-2 using HARK, our open-sourced robot audition software. Preliminary results show that the soft MFM outperformed a hard (binary) MFM in recognizing three simultaneous utterances. In a human-robot interaction task, the interval limitations between two adjacent loudspeakers were reduced from 60 degrees to 30 degrees by using soft MFMs.<\/jats:p>","DOI":"10.2478\/s13230-010-0005-1","type":"journal-article","created":{"date-parts":[[2010,3,27]],"date-time":"2010-03-27T10:57:57Z","timestamp":1269687477000},"page":"37-47","source":"Crossref","is-referenced-by-count":0,"title":["Soft missing-feature mask generation for Robot Audition"],"prefix":"10.2478","volume":"1","author":[{"given":"Toru","family":"Takahashi","sequence":"first","affiliation":[{"name":"Department of Intelligence and Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan"}]},{"given":"Kazuhiro","family":"Nakadai","sequence":"additional","affiliation":[{"name":"Honda Research Institute Japan Co., Ltd., 8-1 Honcho, Wako, Saitama 351-0114, Japan"},{"name":"Mechanical and Environmental Informatics, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, Tokyo, 152-8552, Japan"}]},{"given":"Kazunori","family":"Komatani","sequence":"additional","affiliation":[{"name":"Department of Intelligence and Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan"}]},{"given":"Tetsuya","family":"Ogata","sequence":"additional","affiliation":[{"name":"Department of Intelligence and Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan"}]},{"given":"Hiroshi G.","family":"Okuno","sequence":"additional","affiliation":[{"name":"Department of Intelligence and Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan"}]}],"member":"374","published-online":{"date-parts":[[2010,3,31]]},"container-title":["Paladyn, Journal of Behavioral Robotics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.2478\/s13230-010-0005-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.2478\/s13230-010-0005-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.2478\/s13230-010-0005-1\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.2478\/s13230-010-0005-1\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T11:17:02Z","timestamp":1651058222000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.2478\/s13230-010-0005-1\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,3,1]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2010,3,31]]},"published-print":{"date-parts":[[2010,3,1]]}},"alternative-id":["10.2478\/s13230-010-0005-1"],"URL":"https:\/\/doi.org\/10.2478\/s13230-010-0005-1","relation":{},"ISSN":["2081-4836"],"issn-type":[{"value":"2081-4836","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,3,1]]}}}