Using Mel-frequency cepstral coefficients in missing data technique
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jun, Z | - |
dc.contributor.author | Kwong, S | - |
dc.contributor.author | Gang, W | - |
dc.contributor.author | Hong, QY | - |
dc.date.accessioned | 2023-12-08T09:33:29Z | - |
dc.date.available | 2023-12-08T09:33:29Z | - |
dc.date.issued | 2004-03 | - |
dc.identifier.issn | 1110-8657 | - |
dc.identifier.issn | 1687-0433 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/115933 | - |
dc.description.abstract | Filter bank is the most common feature being employed in the research of the marginalisation approaches for robust speech recognition due to its simplicity in detecting the unreliable data in the frequency domain. In this paper, we propose a hybrid approach based on the marginalisation and the soft decision techniques that make use of the Mel-frequency cepstral coefficients (MFCCs) instead of filter bank coefficients. A new technique for estimating the reliability of each cepstral component is also presented. Experimental results show the effectiveness of the proposed approaches. | - |
dc.format.extent | 7 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Hindawi Publishing Corporation | - |
dc.title | Using Mel-frequency cepstral coefficients in missing data technique | - |
dc.type | Article | - |
dc.publisher.location | 이집트 | - |
dc.identifier.doi | 10.1155/S1110865704309030 | - |
dc.identifier.scopusid | 2-s2.0-2142777887 | - |
dc.identifier.wosid | 000221001700002 | - |
dc.identifier.bibliographicCitation | Eurasip Journal on Applied Signal Processing, v.2004, no.3, pp 340 - 346 | - |
dc.citation.title | Eurasip Journal on Applied Signal Processing | - |
dc.citation.volume | 2004 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 340 | - |
dc.citation.endPage | 346 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | AUTOMATIC SPEECH RECOGNITION | - |
dc.subject.keywordPlus | NOISE | - |
dc.subject.keywordAuthor | MFCC | - |
dc.subject.keywordAuthor | missing data techniques | - |
dc.subject.keywordAuthor | robust speech recognition | - |
dc.identifier.url | https://link.springer.com/article/10.1155/s1110865704309030?utm_source=getftr&utm_medium=getftr&utm_campaign=getftr_pilot | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.