MPE-based discriminative linear transform for speaker adaptation

We present a discriminative method for speaker adaptation, where the minimum phone error (MPE) criterion is used to estimate the discriminative linear transforms (DLTs), including both 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 a previously proposed discriminative method for transform estimation. Preliminary experiments on unsupervised DLT estimation are also reported for conversational telephone speech transcription.