Sinusoidal modeling using wavelet packet transform applied to the analysis and synthesis of speech signals

Kihong Kim, Jinkeun Hong, Jongin Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The sinusoidal model has proven useful for representation and modification of speech and audio signal. One drawback, however, is that a sinusoidal model is typically derived using a fixed analysis frame size. It cannot guarantee an optimal spectral resolution to each sinusoidal parameter. In this paper, we propose a sinusoidal model using wavelet packet analysis, to obtain better frequency resolution at low frequencies and better time resolution at high frequencies and to estimate the sinusoidal parameters more accurately. Experiments show that the proposed model can achieve better performance than conventional model.

Original languageEnglish
Title of host publicationText, Speech and Dialogue - 8th International Conference, TSD 2005, Proceedings
PublisherSpringer Verlag
Pages241-248
Number of pages8
ISBN (Print)3540287892, 9783540287896
DOIs
Publication statusPublished - 2005 Jan 1
Event8th International Conference on Text, Speech and Dialogue, TSD 2005 - Karlovy Vary, Czech Republic
Duration: 2005 Sep 122005 Sep 15

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3658 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Text, Speech and Dialogue, TSD 2005
CountryCzech Republic
CityKarlovy Vary
Period05/9/1205/9/15

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kim, K., Hong, J., & Lim, J. (2005). Sinusoidal modeling using wavelet packet transform applied to the analysis and synthesis of speech signals. In Text, Speech and Dialogue - 8th International Conference, TSD 2005, Proceedings (pp. 241-248). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3658 LNAI). Springer Verlag. https://doi.org/10.1007/11551874_31