A Rule Based Prosody Model for Turkish Text-To Synthesis

Abstract

This paper presents our novel prosody model in a Turkish text-to-speech synthesis (TTS) system. After developing a TTS system driven by parametric features consisting of duration, pitch and energy modifications, we try to figure out some prosody rules in order to increase the naturalness of our synthesizer. Since the inflected verbs in Turkish can be stand-alone sentences with the suffixes they take, we build a perceptual prosody model by defining rules on the stress patterns of verb inflections. Affirmative, negative and interrogative (both positive and negative) forms of many verbs were examined in a systematic way. Not only verbs, but in the same way, some phrases were examined for obtaining a proper prosody. According to the results of listening tests, the defined rules based on duration, pitch and energy modification weights, result in perceptually better speech synthesis, namely about 1,78/5,0 improvement in average in the CMOS (Comparative Mean Opinion Score) test. This improvement shows the success of our novel prosody model.