Dual-microphone voice activity detection based on using optimally weighted maximum a posteriori probabilities
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Huang, Seng Hyun | - |
dc.contributor.author | Park, Jihwan | - |
dc.contributor.author | Chang, Joon-Hyuk | - |
dc.date.accessioned | 2021-08-02T16:53:07Z | - |
dc.date.available | 2021-08-02T16:53:07Z | - |
dc.date.created | 2021-05-13 | - |
dc.date.issued | 2016-05 | - |
dc.identifier.issn | 0736-7791 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/23086 | - |
dc.description.abstract | In this paper, we propose to improve the dual-microphone voice activity detection (VAD) technique for which a discriminative weight training is applied to achieve optimally weighted spatial features. In our approach, we first derive the maximum a posteriori (MAP) probabilities from the spatial features such as the power level difference ratio (PLDR), phase vector, and coherence. Then, we combine each MAP probability within the minimum classification error (MCE) framework to offer an optimal VAD decision in a spectral domain. Experimental results show that the proposed dual-microphone VAD algorithm shows better performances than the conventional dual-microphone VAD methods, which solely utilize the PLDR, phase, and spectral coherence. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Dual-microphone voice activity detection based on using optimally weighted maximum a posteriori probabilities | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Chang, Joon-Hyuk | - |
dc.identifier.doi | 10.1109/ICASSP.2016.7472701 | - |
dc.identifier.scopusid | 2-s2.0-84973305053 | - |
dc.identifier.bibliographicCitation | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, v.2016-May, pp.5360 - 5364 | - |
dc.relation.isPartOf | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | - |
dc.citation.title | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | - |
dc.citation.volume | 2016-May | - |
dc.citation.startPage | 5360 | - |
dc.citation.endPage | 5364 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | maximum likelihood estimation | - |
dc.subject.keywordPlus | microphones | - |
dc.subject.keywordPlus | speech recognition | - |
dc.subject.keywordAuthor | discriminative weight training | - |
dc.subject.keywordAuthor | dual-microphone | - |
dc.subject.keywordAuthor | minimum classification error | - |
dc.subject.keywordAuthor | Voice activity detection | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/7472701 | - |
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