Name
Title | ||
|---|---|---|
Rapid Feature Space Speaker Adaptation for Multi-Stream HMM-Based Audio-Visual Speech Recognition |
Abstract | ||
|---|---|---|
Multi-stream hidden Markov models (HMMs) have recently been very successful in audio-visual speech recognition, where the audio and visual streams are fused at the final decision level. In this paper we investigate fast feature space speaker adaptation using multi-stream HMMs for audio-visual speech recognition. In particular, we focus on studying the performance of feature-space maximum likelihood linear regression (fMLLR), a fast and effective method for estimating feature space transforms. Unlike the common speaker adaptation techniques of MAP or MLLR, fMLLR does not change the audio or visual HMM parameters, but simply applies a single transform to the testing features. We also address the problem of fast and robust on-line fMLLR adaptation using feature space maximum a posterior linear regression (fMAPLR). Adaptation experiments are reported on the IBM infrared headset audio-visual database. On average for a 20-speaker 1 hour independent test set, the multi-stream fMLLR achieves 31% relative gain on the clean audio condition, and 59% relative gain on the noisy audio condition (approximately 7 dB) as compared to the baseline multi-stream system |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ICME.2005.1521429 | ICME |
Keywords | Field | DocType |
speech recognition,audio-visual database,regression analysis,maximum likelihood estimation,fmllr,feature space maximum likelihood linear regression,speaker recognition,feature extraction,audio databases,speaker adaptation technique,multistream hmm,video databases,ibm infrared headset,hidden markov models,hidden markov model,linear regression,testing,feature space,robustness | Feature vector,Pattern recognition,Computer science,FMLLR,Feature extraction,Speech recognition,Robustness (computer science),Speaker recognition,Audio-visual speech recognition,Artificial intelligence,Hidden Markov model,Test set | Conference |
ISBN | Citations | PageRank |
0-7803-9331-7 | 5 | 0.57 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing Huang | 1 | 2464 | 186.09 |
| Etienne Marcheret | 2 | 100 | 11.15 |
| Karthik Visweswariah | 3 | 400 | 38.22 |