Optimization of a neural network for speaker and task dependent F 0-generation

The generation of a pleasant pitch contour is an important issue for the naturalness of each TTS system. Until now the results are far from being satisfactory. We present a speaker and task specific approach realized by a neural network. Personal and task specific characteristics are maintained and the demand of generalization decreases. Therefore the results in application can significantly be improved. Using an optimized network structure global and well localized patterns can be covered and trained simultaneously within one network. Correlation analysis of the data base versus the sensitivity of the trained network validates the importance of distinctive parameters in training. Based on this comparison we discuss the generalization properties of the NN trained speaker and task dependency. Finally a variation of the context range helps to find an optimized tuning of the input parameter set