A speech recognition method, comprising receiving a speech input from a new speaker which comprises a sequence of observations and determining the likelihood of a sequence of words arising from the sequence of observations using an acoustic model and a language model, comprising providing an acoustic model for performing speech recognition on a input signal which comprises a sequence of observations, wherein said model has been trained to recognize speech from a different speaker or speakers. The model has a plurality of model parameters relating to the probability distribution of a word or part thereof being related to an observation and the model trained for a different speaker or speakers is adapted to the new speaker. The speech recognition method further comprises determining the likelihood of a sequence of observations occurring in a given language using a language model and combining the likelihoods determined by the acoustic model and the language model and outputting a sequence of words identified from said speech input signal. Adapting the model to the new speaker comprises calculating adaptive statistics, said adaptive statistics being generated by comparing the speech of the new speaker with that of the acoustic model trained for other speakers; determining prior statistics, said prior statistics derived from a prior transform which models the differences between speakers based on heuristic knowledge of the differences in acoustic realizations between speakers and interpolating said adaptive statistics and selected prior statistics to produce smoothed statistics and using said smoothed statistics to estimate a new transform and applying said transform to said model.
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