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dc.contributor.authorJuang, Biing-Hwang (Fred)
dc.contributor.authorWatanabe, Shinji
dc.date.accessioned2019-04-26T16:51:07Z
dc.date.available2019-04-26T16:51:07Z
dc.date.issued2011-09
dc.identifier.urihttp://hdl.handle.net/1853/61009
dc.descriptionIssued as final reporten_US
dc.description.abstractThis research focus is motivated by the general issue of robust acoustic modeling of speech for achieving superior and reliable performance across various application environments. In real environments, characteristics of a speech signal vary considerably, due to changes of contents, speakers, and ambience. There is thus an acute need in the methodology for the construction of robust and high-accuracy speech models that adaptively respond to these changes of the environment. In particular, the approach that is being taken in this collaboration is based on discriminative modeling. We aim to apply our studies and new techniques to the task of speaker diarization and acoustic event detection in addition to speech recognition.en_US
dc.description.sponsorshipNippon Telegraph and Telephone Corporationen_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.relation.ispartofseriesSchool of Electrical and Computer Engineering ; Project no. 114452en_US
dc.subjectAcoustic modelingen_US
dc.subjectDiscriminative trainingen_US
dc.subjectSpeech recognitionen_US
dc.titleAdaptive & discriminative speech modeling to cope with temporal changes of environmentsen_US
dc.typeTechnical Reporten_US
dc.contributor.corporatenameGeorgia Institute of Technology. Office of Sponsored Programsen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Electrical and Computer Engineeringen_US


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