Sixth European Conference on Speech Communication and Technology
This paper presents an approach for fast, unsupervised, on-line MLLR speaker adaptation using two MAP-like weighting schemes, a static and a dynamic one. While for the standard MLLR approach several sentences are necessary before a reliable estimation of the transformations is possible, the weighted approach shows good results even if adaptation is conducted after only a few short utterances. Experimental results show that using the static approach can improve the word error rate by approx. 27% if adaptation is conducted after every 4 utterances (single words or short phrases). Using the dynamic approach, results can be improved by 28%. The most important advantage of the dynamic weight is that it is rather insensitive with respect to the initial weight whereas for the static approach it is very critical which initial weight to chose. Moreover, useful values for the weights in the static case depend very much on the corpus. If the standard MLLR approach is used, even a drastic increase in sentence error rate can be observed for these small amounts of adaptation data.
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Bibliographic reference. Goronzy, Silke / Kompe, Ralf (1999): "A MAP-like weighting scheme for MLLR speaker adaptation", In EUROSPEECH'99, 5-8.