A high-performance Min-Nan/Taiwanese TTS system

The implementation of a high-performance Min-Nan/Taiwanese TTS system is presented. The system can convert both Min-Nan/Taiwanese texts, represented in a hybrid Han-Lo written form, and Chinese texts into natural Taiwanese speech. It is an improved version of the system developed previously (Huang, J.Y., "Implementation of Tone Sandhi Rules and Tagger for Taiwanese TTS", Master Thesis, Commun. Eng. Dept., National Chiao Tung Univ., 2001). Improvements include: the addition of a "Chinese-to-Min-Nan/Taiwanese" lexicon to solve the OOV problem and to increase the ability of processing Chinese text; the use of explicit tone sandhi rules to ease the learning of prosody generation; a further processing of the training database to detect all breaks not associated with PMs; and the use of four RNNs (recurrent neural nets) to generate four types of prosodic parameters separately. The system is implemented by software and runs in real-time on a PC. An informal subjective listening test confirmed that the system performed well. All synthetic speech sounded natural for well-tokenized Min-Nan/Taiwanese texts and for automatically tokenized Chinese texts.