| 摘要 |
PURPOSE:To drive a phoneme context dependence type phoneme model by driving an HMM(Hidden Markov Model) phoneme matching part which matches a phoneme sentence by using a phoneme context dependent HMM phoneme model matching a predicted phoneme context and finding the presence probability of the predicted phoneme. CONSTITUTION:A phoneme context prediction part 107 predicts the phoneme context of a phoneme predicted by a predictive LR (Left to Right) parser part 108, the phoneme context dependence type phoneme model 102 matching the environment of the phoneme context is driven, and the presence probability of the phoneme predicted is driven, and the presence probability of the phoneme predicted by the phoneme context prediction part 107 is found by driving the HMM phoneme matching part 101. Namely, a phoneme in input speech data is predicted by using an LR table 106, the phoneme context prediction part 107 predicts the phoneme context of the periphery of the predicted phoneme by using the LR table 106, and the prediction result is verified by the phoneme matching function of an HMM phoneme recognition part. Consequently, the phoneme context dependency type HMM phoneme model 102 corresponding to an LR parser phoneme context can be driven. |
