Speech processing using higher order statistics

Ines Jebali Gdoura; Philipos Loizou; Andreas Spanias

Speech processing using higher order statistics

Ines Jebali Gdoura, Philipos Loizou, Andreas Spanias

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

This paper examines the potential use of third-order statistics (TOS) in speech processing applications. In particular, we consider a source-system speech representation and an analysis algorithm that computes the autoregressive (AR) parameters of speech from its third-order cumulants. The TOS-based AR estimates are compared with those obtained using second order statistics. Results are given for voiced and unvoiced speech segments which are corrupted by additive Gaussian noise. The TOS-based AR estimation algorithm is also used to estimate the parameters of the short-term prediction filter of a code excited linear prediction (CELP) algorithm.

Original language	English (US)
Title of host publication	Proceedings - IEEE International Symposium on Circuits and Systems
Publisher	Publ by IEEE
Pages	160-163
Number of pages	4
ISBN (Print)	0780312813
State	Published - 1993
Event	1993 IEEE International Symposium on Circuits and Systems - Chicago, IL, USA Duration: May 3 1993 → May 6 1993

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	1
ISSN (Print)	0271-4310

Other

Other	1993 IEEE International Symposium on Circuits and Systems
City	Chicago, IL, USA
Period	5/3/93 → 5/6/93

ASJC Scopus subject areas

Electrical and Electronic Engineering

Cite this

Speech processing using higher order statistics. / Gdoura, Ines Jebali; Loizou, Philipos; Spanias, Andreas.
Proceedings - IEEE International Symposium on Circuits and Systems. Publ by IEEE, 1993. p. 160-163 (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - This paper examines the potential use of third-order statistics (TOS) in speech processing applications. In particular, we consider a source-system speech representation and an analysis algorithm that computes the autoregressive (AR) parameters of speech from its third-order cumulants. The TOS-based AR estimates are compared with those obtained using second order statistics. Results are given for voiced and unvoiced speech segments which are corrupted by additive Gaussian noise. The TOS-based AR estimation algorithm is also used to estimate the parameters of the short-term prediction filter of a code excited linear prediction (CELP) algorithm.

AB - This paper examines the potential use of third-order statistics (TOS) in speech processing applications. In particular, we consider a source-system speech representation and an analysis algorithm that computes the autoregressive (AR) parameters of speech from its third-order cumulants. The TOS-based AR estimates are compared with those obtained using second order statistics. Results are given for voiced and unvoiced speech segments which are corrupted by additive Gaussian noise. The TOS-based AR estimation algorithm is also used to estimate the parameters of the short-term prediction filter of a code excited linear prediction (CELP) algorithm.

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M3 - Conference contribution

AN - SCOPUS:0027151684

SN - 0780312813

T3 - Proceedings - IEEE International Symposium on Circuits and Systems

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BT - Proceedings - IEEE International Symposium on Circuits and Systems

PB - Publ by IEEE

T2 - 1993 IEEE International Symposium on Circuits and Systems

Y2 - 3 May 1993 through 6 May 1993

ER -

Speech processing using higher order statistics

Abstract

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