A variational EM method for pole-zero modeling of speech with mixed block sparse and Gaussian excitation

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Abstract

The modeling of speech can be used for speech synthesis and speech recognition. We present a speech analysis method based on pole-zero modeling of speech with mixed block sparse and Gaussian excitation. By using a pole-zero model, instead of the all-pole model, a better spectral fitting can be expected. Moreover, motivated by the block sparse glottal flow excitation during voiced speech and the white noise excitation for unvoiced speech, we model the excitation sequence as a combination of block sparse signals and white noise. A variational EM (VEM) method is proposed for estimating the posterior PDFs of the block sparse residuals and point estimates of mod- elling parameters within a sparse Bayesian learning framework. Compared to conventional pole-zero and all-pole based methods, experimental results show that the proposed method has lower spectral distortion and good performance in reconstructing of the block sparse excitation.
Original languageEnglish
Title of host publicationThe 25th European Signal Processing Conference (EUSIPCO 2017)
Number of pages5
PublisherIEEE
Publication date28 Aug 2017
Pages1784-1788
ISBN (Print)978-0-9928626-7-1
DOIs
Publication statusPublished - 28 Aug 2017
Event25th European Signal Processing Conference 2017 - Kos International Convention Center, Kos, Greece
Duration: 28 Aug 20172 Sep 2017
Conference number: 25
https://www.eusipco2017.org/#

Conference

Conference25th European Signal Processing Conference 2017
Number25
LocationKos International Convention Center
CountryGreece
CityKos
Period28/08/201702/09/2017
Internet address
SeriesProceedings of the European Signal Processing Conference
ISSN2076-1465

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