|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
MPE-BASED DISCRIMINATIVE LINEAR TRANSFORM FOR SPEAKER ADAPTATION
L. Wang and P.C. Woodland
In this paper, we present a discriminative method for speaker adaptation, where the minimum phone error (MPE) criterion is used to estimate the discriminative linear transform (DLT), including mean and diagonal variance transforms. The I-smoothing technique is essential to improve the generalization of DLTs. Experiments on supervised adaptation for non-native speakers on the North American Business (NAB) Spoke 3 task show that MPE-based DLT outperforms both MLLR and previously proposed discriminative method for transform estimation. Preliminary experiments on unsupervised DLT estimation are plotted on conversational telephone speech transcription.
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