A speech enhancement algorithm based on β-order GARCH model

Author

Xian-bo Meng ; Chang-chun Bao ; Bing-Yin Xia

Author_Institution

Speech & Audio Signal Process., Beijing Univ. of Technol., Beijing, China

fYear

2013

fDate

6-10 July 2013

Firstpage

342

Lastpage

346

Abstract

This paper presents a novel speech enhancement algorithm based on β-order GARCH (Generalized Auto-regressive Conditional Heteroscedasticity) model. The speech signal is modeled as β-order GARCH process, and the a priori SNR is estimated effectively. The noisy signal is divided into several critical bands, and then the value of order β is updated adaptively according to the signal-to-noise ratios in each critical band. Besides, a novel estimation method for the parameters of β-order GARCH model is proposed in this paper. The performance of the proposed algorithm is evaluated under the standard of ITU-T G.160. The experimental results show that, in comparison with the reference method, the proposed algorithm can get a greater noise reduction and larger SNR improvement, better enhanced speech quality is also ensured in different noise environments.

Keywords

autoregressive processes; signal denoising; speech enhancement; β-order GARCH model; ITU-T G.160 standard; a priori SNR; enhanced speech quality; generalized autoregressive conditional heteroscedasticity model; noise environments; noise reduction; noisy signal; parameter estimation method; signal-to-noise ratio; speech enhancement algorithm; Adaptation models; Noise measurement; Signal to noise ratio; Speech; Speech enhancement; White noise; β-order GARCH model; a priori SNR estimation; model parameter estimation; speech enhancement;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal and Information Processing (ChinaSIP), 2013 IEEE China Summit & International Conference on

Conference_Location

Beijing

Type

conf

DOI

10.1109/ChinaSIP.2013.6625357

Filename

6625357