Sixth International Conference on Spoken Language Processing
The principle of the eigenvoice method - using a priori knowledge on the speaker variability as collected during the training for a very fast adaptation - is applied to continuous speech recognition with large vocabulary. The handling of mixture density HMM models is discussed. For the case of gender independent models, a decrease of the word error rate of up to 15% is observed for unsupervised adaptation and even the first recognized phonemes lead to considerable improvements. The first two eigenvectors of adaptation can be characterized as classifying the gender and the recording environment. Comparisons of the method with MLLR are done as far as the latter is applicable at all.
Bibliographic reference. Botterweck, Henrik (2000): "Very fast adaptation for large vocabulary continuous speech recognition using eigenvoices", In ICSLP-2000, vol.4, 354-357.