Title :
Recursive estimation based on the trended hidden Markov model in speech enhancement
Author :
Lee, Ki Yong ; Rheem, Jae Yeol ; Shirai, K.
Author_Institution :
Dept. of Electron. Eng., Changwon Nat. Univ., Kyengnam, South Korea
Abstract :
In this study, we propose a new speech enhancement based on the trended HMM. The trended HMM is a nonstationary state HMM for modeling nonstationary speech. The proposed method is a recursive method based on frame-by-frame using a Kalman filter with LP parameters controlled by a Markov switching sequence. Experimental results clearly show the superior performance of the proposed method over the standard HMM based method
Keywords :
Kalman filters; hidden Markov models; recursive estimation; speech enhancement; Kalman filter; LP parameters; Markov switching sequence; frame-by-frame technique; nonstationary speech; nonstationary state HMM; recursive estimation; speech enhancement; trended HMM; trended hidden Markov model; Acoustic noise; Computer science education; Educational technology; Hidden Markov models; Recursive estimation; Speech analysis; Speech enhancement; Speech processing; State estimation; White noise;
Conference_Titel :
Circuits and Systems, 1996., IEEE Asia Pacific Conference on
Conference_Location :
Seoul
Print_ISBN :
0-7803-3702-6
DOI :
10.1109/APCAS.1996.569263
