5th International Conference on Spoken Language Processing
Energy contour in a sentence is one of major factors that affect the naturalness of synthetic speech. In this paper. we propose a method to control the energy contour for the enhancement in the naturalness of Korean synthetic speech. Our algorithm adopts syllable as a basic unit and predicts the peak amplitude for each syllable in a word using a neural network (NN). We utilize indirect linguistic features as well as acoustic features of phonemes as input data to the NN to accommodate the grammatical effects of words in a sentence. The simulation results show that prediction error is less than 10% and our algorithm is very effective for analysis/synthesis of the energy contour of a sentence.. and generates a fairly good declarative contour for TTS.
Bibliographic reference. Lee, Jungchul / Kang, Donggyu / Kim, Sanghoon / Sung, Koengmo (1998): "Energy contour generation for a sentence using a neural network learning method", In ICSLP-1998, paper 0404.