Title :
The employment of Bayesian method in noise: Reduction and packet loss replacement
Author :
Rahimi, Azar ; Ghorshi, Seyed ; Sarafnia, Ali
Author_Institution :
Sch. of Sci. & Eng., Sharif Univ. of Technol., Tehran, Iran
Abstract :
Speech enhancement in real-time applications improves the quality and intelligibility of the speech and reduces communication fatigue. Nowadays, due to reactivity of the systems and spread of online real-time applications, including VoIP, state-space models have been used broadly. This paper presents a speech enhancement method based on adaptive Bayesian-Kalman filter and Bayesian-MAP estimation to improve the performance and the quality of the enhancement procedure. The enhancement method includes a combination of Bayesian-Kalman filter for noise reduction and Bayesian-MAP estimation for parameter estimation of the lost speech segments. Performance evaluation and result of the proposed method indicates the efficiency of this method compared to other method.
Keywords :
Bayes methods; Kalman filters; parameter estimation; real-time systems; speech enhancement; Bayesian method employment; Bayesian-MAP estimation; VoIP; adaptive Bayesian-Kalman filter; noise reduction; online real-time applications; packet loss replacement; parameter estimation; real-time applications; reduction loss replacement; speech enhancement; state-space models; Bayes methods; Estimation; Kalman filters; Loss measurement; Noise reduction; Speech; Speech enhancement; Bayesian Kalman Filter; Bayesian MAP Estimation; PLC; Speech Enhancement;
Conference_Titel :
ELMAR, 2013 55th International Symposium
Conference_Location :
Zadar
Print_ISBN :
978-953-7044-14-5