Speaker Recognition With Session Variability Normalization Based on MLLR Adaptation Transforms

We present a new modeling approach for speaker recognition that uses the maximum-likelihood linear regression (MLLR) adaptation transforms employed by a speech recognition system as features for support vector machine (SVM) speaker models. This approach is attractive because, unlike standard frame-based cepstral speaker recognition models, it normalizes for… CONTINUE READING

13 Figures & Tables


Citations per Year

84 Citations

Semantic Scholar estimates that this publication has 84 citations based on the available data.

See our FAQ for additional information.