Digit recognition in noisy environments via a sequential GMM/SVM system

Fine, Saon, Gopinath
2002 IEEE International Conference on Acoustics Speech and Signal Processing  
This paper exploits the fact that when GMM and SVM classifiers with roughly the same level of performance exhibit uncorrelated errors they can be combined to produce a better classifier. The gain accrues from combining the descriptive strength of GMM models with the discriminative power of SVM classifiers. This idea, first exploited in the context of speaker recognition [1, 2] , is applied to speech recognition -specifically to a digit recognition task in a noisy environment -with significant gains in performance.
doi:10.1109/icassp.2002.1005672 fatcat:oyke2htd6ba5jjfodaj6ixhbqy