We present two approaches to generate F0 contours for German utterances based on a phonological transcription of the utterances (phonetic string, accents, and phrase boundaries). The first approach uses a data base of natural F0 patterns which are concatenated to new Fo contours. The second one uses a recurrent neural network to produce global F0 contours directly from the encoded phonological transcription. Our results show that both approaches are well-suited to produce high-quality F0 contours. So far, the resulting contours produced with the neural network are better than the ones produces with the patterns data base. Using a neural network for the generation of complete F0 contours with high quality is feasible and may require much less human effort than other approaches.
Cite as: Traber, C. (1990) F0 generation with a data base of natural F0 patterns and with a neural network. Proc. First ESCA Workshop on Speech Synthesis (SSW 1), 141-144
@inproceedings{traber90_ssw,
author={Christof Traber},
title={{F0 generation with a data base of natural F0 patterns and with a neural network}},
year=1990,
booktitle={Proc. First ESCA Workshop on Speech Synthesis (SSW 1)},
pages={141--144}
}