A nonlinear unsupervised adaptation technique for speech recognition
Satya Dharanipragada, Mukund Padmanabhan · 2000
This paper describes a computationally inexpensive, nonlinear feature transformation technique for rapid adaptation of a speech recognition system to new acoustic conditions. One of the advantages of the method is that it does not require any initial decoding of the adaptation data for computing the nonlinear transform. This technique performs as well as the more expensive unsupervised MLLR technique. Furthermore, it signi cantly adds to the improvement when combined with unsupervised MLLR. 1.