Mixture IMM for speech enhancement under nonstationary noise

Mixture IMM for speech enhancement under nonstationary noise

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...

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Veröffentlicht in:IEEE transactions on speech and audio processing 2000-09, Vol.8 (5), p.637-641
Hauptverfasser: Kang, SangKi, Baek, SeongJoon, Lee, Ki Yong, Sung, Koeng-Mo
Format: Artikel
Sprache:eng
Schlagworte:
Additive noise
Algorithms
Cleaning
Colored noise
Contamination
Filters
Gain
Gaussian noise
Gaussian processes
Mathematical models
Noise
Performance gain
Recursive estimation
Signal processing
Sound filters
Speech
Speech enhancement
Speech processing
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Beschreibung
Zusammenfassung: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.
ISSN:1063-6676
2329-9290
1558-2353
2329-9304
DOI:10.1109/89.861391