Short-time extraction mel-cepstra Context feature selection HMM state extraction Phoneme segmentation probabilities classification HMM state

Determination of the error rate In the speech database collected here mostly in 1995, there are currently data of 20 speakers and at least four recording sessions of 350 Finnish words for each speaker. The speaker dependent recognition models are trained using three word sets and tested by the remaining one. The error rate given as the result is the number of all phoneme errors (inserted,deleted and changed phonemes) divided by the total number of phonemes. To gain statistical significance for the model comparisons, the tests are normally made for seven different speakers and the error rates are averaged. For verifying the robustness of the models for slightly different speech data also an older database (from 1990) is sometimes used. In general, the older database gives lower average error rates, probably because of the more experienced speakers. For comparisons of the models the post-processing by the Dynamically Expanding Context (DEC) [1]is not applied in order