Least 1-Norm Pole-Zero Modeling with Sparse Deconvolution for Speech Analysis

Liming Shi; Jesper Rindom Jensen; Mads Græsbøll Christensen

doi:10.1109/ICASSP.2017.7952252

Least 1-Norm Pole-Zero Modeling with Sparse Deconvolution for Speech Analysis

Liming Shi, Jesper Rindom Jensen, Mads Græsbøll Christensen

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

7 Citationer (Scopus)

334 Downloads (Pure)

Abstract

In this paper, we present a speech analysis method based on sparse pole-zero modeling of speech. Instead of using the all-pole model to approximate the speech production filter, a pole-zero model is used for the combined effect of the vocal tract; radiation at the lips and the glottal pulse shape. Moreover, to consider the spiky excitation form of the pulse train during voiced speech, the modeling parame- ters and sparse residuals are estimated in an iterative fashion using a least 1-norm pole-zero with sparse deconvolution algorithm. Com- pared with the conventional two-stage least squares pole-zero, linear prediction and sparse linear prediction methods, experimental results show that the proposed speech analysis method has lower spectral distortion, higher reconstruction SNR and sparser residuals.

Originalsprog	Engelsk
Titel	IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
Antal sider	5
Forlag	IEEE
Publikationsdato	19 jun. 2017
Sider	731-735
ISBN (Elektronisk)	978-1-5090-4117-6
DOI	https://doi.org/10.1109/ICASSP.2017.7952252
Status	Udgivet - 19 jun. 2017
Begivenhed	The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing: The Internet of Signals - New Orleans, USA Varighed: 5 mar. 2017 → 9 mar. 2017 http://www.ieee-icassp2017.org/ http://www.ieee-icassp2017.org/

Konference

Konference	The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing
Land/Område	USA
By	New Orleans
Periode	05/03/2017 → 09/03/2017
Internetadresse	http://www.ieee-icassp2017.org/ http://www.ieee-icassp2017.org/

Navn	I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings
ISSN	1520-6149

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10.1109/ICASSP.2017.7952252

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Citationsformater

@inproceedings{538fb7a44f354528a0964715be16242e,

title = "Least 1-Norm Pole-Zero Modeling with Sparse Deconvolution for Speech Analysis",

abstract = "In this paper, we present a speech analysis method based on sparse pole-zero modeling of speech. Instead of using the all-pole model to approximate the speech production filter, a pole-zero model is used for the combined effect of the vocal tract; radiation at the lips and the glottal pulse shape. Moreover, to consider the spiky excitation form of the pulse train during voiced speech, the modeling parame- ters and sparse residuals are estimated in an iterative fashion using a least 1-norm pole-zero with sparse deconvolution algorithm. Com- pared with the conventional two-stage least squares pole-zero, linear prediction and sparse linear prediction methods, experimental results show that the proposed speech analysis method has lower spectral distortion, higher reconstruction SNR and sparser residuals.",

keywords = "Pole-zero model, least 1-norm cost function , sparse deconvolution, speech analysis",

author = "Liming Shi and Jensen, {Jesper Rindom} and Christensen, {Mads Gr{\ae}sb{\o}ll}",

year = "2017",

month = jun,

day = "19",

doi = "10.1109/ICASSP.2017.7952252",

language = "English",

series = "I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings",

publisher = "IEEE",

pages = "731--735",

booktitle = "IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017",

address = "United States",

note = "The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing : The Internet of Signals, ICASSP2017 ; Conference date: 05-03-2017 Through 09-03-2017",

url = "http://www.ieee-icassp2017.org/, http://www.ieee-icassp2017.org/",

}

Shi, L, Jensen, JR & Christensen, MG 2017, Least 1-Norm Pole-Zero Modeling with Sparse Deconvolution for Speech Analysis. i IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017. IEEE, I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings, s. 731-735, The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans, USA, 05/03/2017. https://doi.org/10.1109/ICASSP.2017.7952252

Least 1-Norm Pole-Zero Modeling with Sparse Deconvolution for Speech Analysis. / Shi, Liming; Jensen, Jesper Rindom ; Christensen, Mads Græsbøll.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017. IEEE, 2017. s. 731-735 (I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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N2 - In this paper, we present a speech analysis method based on sparse pole-zero modeling of speech. Instead of using the all-pole model to approximate the speech production filter, a pole-zero model is used for the combined effect of the vocal tract; radiation at the lips and the glottal pulse shape. Moreover, to consider the spiky excitation form of the pulse train during voiced speech, the modeling parame- ters and sparse residuals are estimated in an iterative fashion using a least 1-norm pole-zero with sparse deconvolution algorithm. Com- pared with the conventional two-stage least squares pole-zero, linear prediction and sparse linear prediction methods, experimental results show that the proposed speech analysis method has lower spectral distortion, higher reconstruction SNR and sparser residuals.

AB - In this paper, we present a speech analysis method based on sparse pole-zero modeling of speech. Instead of using the all-pole model to approximate the speech production filter, a pole-zero model is used for the combined effect of the vocal tract; radiation at the lips and the glottal pulse shape. Moreover, to consider the spiky excitation form of the pulse train during voiced speech, the modeling parame- ters and sparse residuals are estimated in an iterative fashion using a least 1-norm pole-zero with sparse deconvolution algorithm. Com- pared with the conventional two-stage least squares pole-zero, linear prediction and sparse linear prediction methods, experimental results show that the proposed speech analysis method has lower spectral distortion, higher reconstruction SNR and sparser residuals.

KW - Pole-zero model

KW - least 1-norm cost function

KW - sparse deconvolution

KW - speech analysis

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Least 1-Norm Pole-Zero Modeling with Sparse Deconvolution for Speech Analysis

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