Title :
Mixture IMM for speech enhancement under nonstationary noise
Author :
Kang, SangKi ; Baek, Seongjoon ; Lee, Ki Yong ; Sung, Koeng-Mo
Author_Institution :
Sch. of Electr. Eng., Seoul Nat. Univ., South Korea
fDate :
9/1/2000 12:00:00 AM
Abstract :
A mixture interacting multiple model (MIMM) algorithm is proposed to enhance speech contaminated by additive nonstationary noise. In this approach, a mixture hidden filter model (HFM) is used for clean speech modeling and a single hidden filter is used for noise process modeling. The MIMM algorithm gives better enhancement results than the IMM algorithm. The results show that the proposed method offers performance gain compared to the previous results in with slightly increased complexity
Keywords :
Kalman filters; Markov processes; acoustic noise; speech enhancement; HFM; MIMM algorithm; additive nonstationary noise; clean speech modeling; complexity; mixture IMM; mixture hidden filter model; mixture interacting multiple model; noise process modeling; nonstationary noise; performance gain; speech enhancement; Additive noise; Colored noise; Filters; Gaussian noise; Gaussian processes; Performance gain; Recursive estimation; Signal processing; Speech enhancement; Speech processing;
Journal_Title :
Speech and Audio Processing, IEEE Transactions on
