Linguistic and Mixed Excitation Improvements on a HMM-based speech synthesis for Castilian Spanish

Abstract

Hidden Markov Models based text-to-speech(HMM-TTS) synthesis is one of the techniques for generating speech from trained statistical models where spectrum and prosody of basic speech units are modelled altogether. This paper presents the advances in our Spanish HMM-TTS and a perceptual test is conducted to compare it with an extended PSOLA-based concatenative (E-PSOLA) system. The improvements have been performed on phonetic information and contextual factors according to the Castilian Spanish language and speech generation using a mixed excitation (ME) technique. The results show the preference of the new HMM-TTS system in front of the previous system and a better MOS in comparison with a real E-PSOLA in terms of acceptability, intelligibility and stability.