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Harmonic Structure Transform for Speaker Recognition
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH. Language Technologies Institute, Carnegie Mellon University, Pittsburgh PA, United States .
2011 (English)In: 12th Annual Conference Of The International Speech Communication Association 2011 (INTERSPEECH 2011), Vols 1-5, ISCA , 2011, 372-375 p.Conference paper (Refereed)
Abstract [en]

We evaluate a new filterbank structure, yielding the harmonic structure cepstral coefficients (HSCCs), on a mismatched-session closed-set speaker classification task. The novelty of the filterbank lies in its averaging of energy at frequencies related by harmonicity rather than by adjacency. Improvements are presented which achieve a 37%rel reduction in error rate under these conditions. The improved features are combined with a similar Mel-frequency cepstral coefficient (MFCC) system to yield error rate reductions of 32%rel, suggesting that HSCCs offer information which is complimentary to that available to today's MFCC-based systems.

Place, publisher, year, edition, pages
ISCA , 2011. 372-375 p.
, Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, ISSN 1990-9772 ; 2011
Keyword [en]
speaker recognition, signal processing, harmonic strucure, spectral analysis
National Category
Language Technology (Computational Linguistics)
URN: urn:nbn:se:kth:diva-137167ISI: 000316502200095ScopusID: 2-s2.0-84865772856ISBN: 978-1-61839-270-1OAI: diva2:679128
12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011; Florence; Italy; 27 August 2011 through 31 August 2011

QC 20131213

Available from: 2013-12-13 Created: 2013-12-11 Last updated: 2013-12-13Bibliographically approved

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Laskowski, Kornel
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