High quality text-to-speech synthesis system with efficient duration models developed using coding schemes based on vowel production characteristics

This paper explores encoding schemes based on production characteristics of vowels. The performance of coding schemes is analyzed for accurate prediction of durations of syllables using neural network models. Linguistic and production constraints represented by positional, contextual, phonological and articulatory (PCPA) features are used for predicting the durations of syllables. These features are coded with distinct numerical values before feeding to the neural network for building models. The evaluation of coding schemes is carried out by means of objective and subjective measures. The quality of text-to-speech synthesis system is observed to be better by incorporating the duration model with vowels coded based on lip roundness.