Korean Prosody Generation Based on Stem-ML

Stem-ML에 기반한 한국어 억양 생성

In this paper, we present a method of generating intonation contour for Korean text-to-speech (TTS) system and a method of synthesizing emotional speech, both based on Soft template mark-up language (Stem-ML), a novel prosody generation model combining mark-up tags and pitch generation in one. The evaluation shows that the intonation contour generated by Stem-ML is better than that by our previous work. It is also found that Stem-ML is a useful tool for generating emotional speech, by controling limited number of tags. Large-size emotional speech database is crucial for more extensive evaluation.