DC Field | Value | Language |
---|---|---|
dc.contributor.author | Suh, Young Joo | ko |
dc.contributor.author | Kim, Hoirin | ko |
dc.date.accessioned | 2013-03-12T17:38:12Z | - |
dc.date.available | 2013-03-12T17:38:12Z | - |
dc.date.created | 2012-08-02 | - |
dc.date.created | 2012-08-02 | - |
dc.date.issued | 2012-08 | - |
dc.identifier.citation | IEEE SIGNAL PROCESSING LETTERS, v.19, no.8, pp.507 - 510 | - |
dc.identifier.issn | 1070-9908 | - |
dc.identifier.uri | http://hdl.handle.net/10203/103036 | - |
dc.description.abstract | In this letter, we propose a novel statistical voice activity detection (VAD) technique. The proposed technique employs probabilistically derived multiple acoustic models to effectively optimize the weights on frequency domain likelihood ratios with the discriminative training approach for more accurate voice activity detection. Experiments performed on various AURORA noisy environments showed that the proposed approach produces meaningful performance improvements over the single acoustic model-based conventional approaches. | - |
dc.language | English | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Multiple Acoustic Model-Based Discriminative Likelihood Ratio Weighting for Voice Activity Detection | - |
dc.type | Article | - |
dc.identifier.wosid | 000305979600001 | - |
dc.identifier.scopusid | 2-s2.0-85008579584 | - |
dc.type.rims | ART | - |
dc.citation.volume | 19 | - |
dc.citation.issue | 8 | - |
dc.citation.beginningpage | 507 | - |
dc.citation.endingpage | 510 | - |
dc.citation.publicationname | IEEE SIGNAL PROCESSING LETTERS | - |
dc.identifier.doi | 10.1109/LSP.2012.2204978 | - |
dc.contributor.localauthor | Kim, Hoirin | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Multiple acoustic models | - |
dc.subject.keywordAuthor | statistical voice activity detection | - |
dc.subject.keywordAuthor | weighted likelihood ratio | - |
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