Name
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 |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/89.861391 | IEEE Transactions on Speech and Audio Processing |
Keywords | Field | DocType |
mixture interacting multiple model,nonstationary noise,kalman filters,performance gain,hfm,acoustic noise,additive nonstationary noise,complexity,mixture hidden filter model,clean speech modeling,speech enhancement,mixture imm,mimm algorithm,markov processes,noise process modeling,process model,gaussian processes,signal processing,speech processing,gaussian noise,colored noise | Speech enhancement,Noise,Markov process,Noise measurement,Pattern recognition,Computer science,Process modeling,Speech recognition,Kalman filter,Speech modeling,Artificial intelligence,Gaussian noise | Journal |
Volume | Issue | ISSN |
8 | 5 | 1063-6676 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sangki Kang | 1 | 1 | 3.06 |
| SeongJoon Baek | 2 | 108 | 12.18 |
| Ki Yong Lee | 3 | 203 | 31.06 |
| Koeng-Mo Sung | 4 | 268 | 35.38 |