Abstract
Original language | English |
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Title of host publication | The 25th European Signal Processing Conference (EUSIPCO 2017) |
Number of pages | 5 |
Publisher | IEEE |
Publication date | 28 Aug 2017 |
Pages | 1784-1788 |
ISBN (Print) | 978-0-9928626-7-1 |
DOIs | |
Publication status | Published - 28 Aug 2017 |
Event | 25th European Signal Processing Conference 2017 - Kos International Convention Center, Kos, Greece Duration: 28 Aug 2017 → 2 Sep 2017 Conference number: 25 https://www.eusipco2017.org/# |
Conference
Conference | 25th European Signal Processing Conference 2017 |
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Number | 25 |
Location | Kos International Convention Center |
Country | Greece |
City | Kos |
Period | 28/08/2017 → 02/09/2017 |
Internet address |
Series | Proceedings of the European Signal Processing Conference |
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ISSN | 2076-1465 |
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A variational EM method for pole-zero modeling of speech with mixed block sparse and Gaussian excitation. / Shi, Liming; Nielsen, Jesper Kjær; Jensen, Jesper Rindom; Christensen, Mads Græsbøll.
The 25th European Signal Processing Conference (EUSIPCO 2017) . IEEE, 2017. p. 1784-1788 (Proceedings of the European Signal Processing Conference).Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
TY - GEN
T1 - A variational EM method for pole-zero modeling of speech with mixed block sparse and Gaussian excitation
AU - Shi, Liming
AU - Nielsen, Jesper Kjær
AU - Jensen, Jesper Rindom
AU - Christensen, Mads Græsbøll
PY - 2017/8/28
Y1 - 2017/8/28
N2 - 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.
AB - 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.
U2 - 10.23919/EUSIPCO.2017.8081516
DO - 10.23919/EUSIPCO.2017.8081516
M3 - Article in proceeding
SN - 978-0-9928626-7-1
T3 - Proceedings of the European Signal Processing Conference
SP - 1784
EP - 1788
BT - The 25th European Signal Processing Conference (EUSIPCO 2017)
PB - IEEE
ER -