| 摘要 |
PURPOSE:To precisely adapt a standard model by the less learning data. CONSTITUTION:The learning data 40 are analysis processed, and viterbi/ segmentation 42 is performed using a standard phoneme model, and a phoneme is separated. By using respective phoneme data, the mean vector of the corresponding standard phoneme model (HMM) 47 is estimated by a maximum after fact probability (MAP) estimation method 43. The mean vector for an unadaptive phoneme model is estimated by an interpolation process of a moving vector field smoothing(VFS) method by using the adaptive phoneme model 44 and the corresponding standard phoneme model 47 45, and the mean vector of the adaptive phoneme model 44 is smoothed by the VFS method 46, and adaptive models 48 making respective mean vectors obtained in the processes 45, 46 and corresponding other parameters the parameters are obtained about respective phonemes. |
