Low Latency and High Quality Two-Stage Human-Voice-Enhancement System for a Hose-Shaped Rescue Robot
[abstFig src='/00290001/19.jpg' width='300' text='Human-voice enhancement system for a hose-shaped robot' ] This paper presents the design and implementation of a two-stage human-voice enhancement system for a hose-shaped rescue robot. When a microphone-equipped hose-sh...
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| Veröffentlicht in: | Journal of robotics and mechatronics 2017-02, Vol.29 (1), p.198-212 |
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| creator | Bando, Yoshiaki Saruwatari, Hiroshi Ono, Nobutaka Makino, Shoji Itoyama, Katsutoshi Kitamura, Daichi Ishimura, Masaru Takakusaki, Moe Mae, Narumi Yamaoka, Kouei Matsui, Yutaro Ambe, Yuichi Konyo, Masashi Tadokoro, Satoshi Yoshii, Kazuyoshi Okuno, Hiroshi G. |
| description | [abstFig src='/00290001/19.jpg' width='300' text='Human-voice enhancement system for a hose-shaped robot' ] This paper presents the design and implementation of a two-stage human-voice enhancement system for a hose-shaped rescue robot. When a microphone-equipped hose-shaped robot is used to search for a victim under a collapsed building, human-voice enhancement is crucial because the sound captured by a microphone array is contaminated by the ego-noise of the robot. For achieving both low latency and high quality, our system combines online and offline human-voice enhancement, providing
an overview first and then details on demand
. The online enhancement is used for searching for a victim in real time, while the offline one facilitates scrutiny by listening to highly enhanced human voices. Our online enhancement is based on an online robust principal component analysis, and our offline enhancement is based on an independent low-rank matrix analysis. The two enhancement methods are integrated with Robot Operating System (ROS). Experimental results showed that both the online and offline enhancement methods outperformed conventional methods. |
| doi_str_mv | 10.20965/jrm.2017.p0198 |
| format | Article |
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an overview first and then details on demand
. The online enhancement is used for searching for a victim in real time, while the offline one facilitates scrutiny by listening to highly enhanced human voices. Our online enhancement is based on an online robust principal component analysis, and our offline enhancement is based on an independent low-rank matrix analysis. The two enhancement methods are integrated with Robot Operating System (ROS). Experimental results showed that both the online and offline enhancement methods outperformed conventional methods.</description><identifier>ISSN: 0915-3942</identifier><identifier>EISSN: 1883-8049</identifier><identifier>DOI: 10.20965/jrm.2017.p0198</identifier><language>eng</language><publisher>Tokyo: Fuji Technology Press Co. Ltd</publisher><subject>Matrix methods ; Principal components analysis ; Robots ; Voice</subject><ispartof>Journal of robotics and mechatronics, 2017-02, Vol.29 (1), p.198-212</ispartof><rights>Copyright © 2017 Fuji Technology Press Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c460t-9be8a9d89640825c0bc40e74c82ef2518358e5214b24f69093fe59caff46208e3</citedby><cites>FETCH-LOGICAL-c460t-9be8a9d89640825c0bc40e74c82ef2518358e5214b24f69093fe59caff46208e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,864,27924,27925</link.rule.ids></links><search><creatorcontrib>Bando, Yoshiaki</creatorcontrib><creatorcontrib>Saruwatari, Hiroshi</creatorcontrib><creatorcontrib>Ono, Nobutaka</creatorcontrib><creatorcontrib>Makino, Shoji</creatorcontrib><creatorcontrib>Itoyama, Katsutoshi</creatorcontrib><creatorcontrib>Kitamura, Daichi</creatorcontrib><creatorcontrib>Ishimura, Masaru</creatorcontrib><creatorcontrib>Takakusaki, Moe</creatorcontrib><creatorcontrib>Mae, Narumi</creatorcontrib><creatorcontrib>Yamaoka, Kouei</creatorcontrib><creatorcontrib>Matsui, Yutaro</creatorcontrib><creatorcontrib>Ambe, Yuichi</creatorcontrib><creatorcontrib>Konyo, Masashi</creatorcontrib><creatorcontrib>Tadokoro, Satoshi</creatorcontrib><creatorcontrib>Yoshii, Kazuyoshi</creatorcontrib><creatorcontrib>Okuno, Hiroshi G.</creatorcontrib><creatorcontrib>Graduate School of Informatics, Kyoto University</creatorcontrib><creatorcontrib>Graduate School of Information Science, Tohoku University</creatorcontrib><creatorcontrib>Graduate School of Information Science and Technology, The University of Tokyo</creatorcontrib><creatorcontrib>National Institute of Informatics</creatorcontrib><creatorcontrib>Department of Informatics, School of Multidisciplinary Sciences, SOKENDAI</creatorcontrib><creatorcontrib>Graduate Program for Embodiment Informatics, Waseda University</creatorcontrib><creatorcontrib>Graduate School of Systems and Information Engineering, Tsukuba University</creatorcontrib><title>Low Latency and High Quality Two-Stage Human-Voice-Enhancement System for a Hose-Shaped Rescue Robot</title><title>Journal of robotics and mechatronics</title><description>[abstFig src='/00290001/19.jpg' width='300' text='Human-voice enhancement system for a hose-shaped robot' ] This paper presents the design and implementation of a two-stage human-voice enhancement system for a hose-shaped rescue robot. When a microphone-equipped hose-shaped robot is used to search for a victim under a collapsed building, human-voice enhancement is crucial because the sound captured by a microphone array is contaminated by the ego-noise of the robot. For achieving both low latency and high quality, our system combines online and offline human-voice enhancement, providing
an overview first and then details on demand
. The online enhancement is used for searching for a victim in real time, while the offline one facilitates scrutiny by listening to highly enhanced human voices. Our online enhancement is based on an online robust principal component analysis, and our offline enhancement is based on an independent low-rank matrix analysis. The two enhancement methods are integrated with Robot Operating System (ROS). Experimental results showed that both the online and offline enhancement methods outperformed conventional methods.</description><subject>Matrix methods</subject><subject>Principal components analysis</subject><subject>Robots</subject><subject>Voice</subject><issn>0915-3942</issn><issn>1883-8049</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNotkE1Lw0AYhBdRsNSevS543nY_k92jlGqEgNhWr2GzedOmNNmYTSj598bqXGYOwww8CD0yuuTURGp16uopsXjZUmb0DZoxrQXRVJpbNKOGKSKM5PdoEcKJTlIyNiKeoSL1F5zaHho3YtsUOKkOR_wx2HPVj3h_8WTX2wPgZKhtQ7585YBsmqNtHNTQ9Hg3hh5qXPoOW5z4AGR3tC0UeAvBDYC3Pvf9A7or7TnA4t_n6PNls18nJH1_fVs_p8TJiPbE5KCtKbSJJNVcOZo7SSGWTnMouWJaKA2KM5lzWUaGGlGCMs6WpYw41SDm6Olvt-389wChz05-6JrpMuMyUpoxIdTUWv21XOdD6KDM2q6qbTdmjGZXmtlEM_ulmV1pih9EC2c8</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Bando, Yoshiaki</creator><creator>Saruwatari, Hiroshi</creator><creator>Ono, Nobutaka</creator><creator>Makino, Shoji</creator><creator>Itoyama, Katsutoshi</creator><creator>Kitamura, Daichi</creator><creator>Ishimura, Masaru</creator><creator>Takakusaki, Moe</creator><creator>Mae, Narumi</creator><creator>Yamaoka, Kouei</creator><creator>Matsui, Yutaro</creator><creator>Ambe, Yuichi</creator><creator>Konyo, Masashi</creator><creator>Tadokoro, Satoshi</creator><creator>Yoshii, Kazuyoshi</creator><creator>Okuno, Hiroshi G.</creator><general>Fuji Technology Press Co. 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Informatics, Kyoto University</aucorp><aucorp>Graduate School of Information Science, Tohoku University</aucorp><aucorp>Graduate School of Information Science and Technology, The University of Tokyo</aucorp><aucorp>National Institute of Informatics</aucorp><aucorp>Department of Informatics, School of Multidisciplinary Sciences, SOKENDAI</aucorp><aucorp>Graduate Program for Embodiment Informatics, Waseda University</aucorp><aucorp>Graduate School of Systems and Information Engineering, Tsukuba University</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Low Latency and High Quality Two-Stage Human-Voice-Enhancement System for a Hose-Shaped Rescue Robot</atitle><jtitle>Journal of robotics and mechatronics</jtitle><date>2017-02-01</date><risdate>2017</risdate><volume>29</volume><issue>1</issue><spage>198</spage><epage>212</epage><pages>198-212</pages><issn>0915-3942</issn><eissn>1883-8049</eissn><abstract>[abstFig src='/00290001/19.jpg' width='300' text='Human-voice enhancement system for a hose-shaped robot' ] This paper presents the design and implementation of a two-stage human-voice enhancement system for a hose-shaped rescue robot. When a microphone-equipped hose-shaped robot is used to search for a victim under a collapsed building, human-voice enhancement is crucial because the sound captured by a microphone array is contaminated by the ego-noise of the robot. For achieving both low latency and high quality, our system combines online and offline human-voice enhancement, providing
an overview first and then details on demand
. The online enhancement is used for searching for a victim in real time, while the offline one facilitates scrutiny by listening to highly enhanced human voices. Our online enhancement is based on an online robust principal component analysis, and our offline enhancement is based on an independent low-rank matrix analysis. The two enhancement methods are integrated with Robot Operating System (ROS). Experimental results showed that both the online and offline enhancement methods outperformed conventional methods.</abstract><cop>Tokyo</cop><pub>Fuji Technology Press Co. Ltd</pub><doi>10.20965/jrm.2017.p0198</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of robotics and mechatronics, 2017-02, Vol.29 (1), p.198-212 |
| issn | 0915-3942 1883-8049 |
| language | eng |
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| source | DOAJ Directory of Open Access Journals; J-STAGE (Japan Science & Technology Information Aggregator, Electronic) Freely Available Titles - Japanese; Open Access Titles of Japan; EZB-FREE-00999 freely available EZB journals |
| subjects | Matrix methods Principal components analysis Robots Voice |
| title | Low Latency and High Quality Two-Stage Human-Voice-Enhancement System for a Hose-Shaped Rescue Robot |
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