Improving an Italian TTS System : Voice Based Rules for Word Boundaries' Phenomena

Abstract: This thesis project aimed at improving a commercial Italian Unit Selection system by obtaining a higher agreement between the internal target representation produced by the text analysis component and the recordings in the speech database. Precisely this has been done by implementing new transformation rules that are applied on the input text during the text normalization and just after the grapheme-to-phoneme (g2p) module. We focused on mismatchings that occur over word boundaries and that are caused by both typical Italian phonotactic phenomena and prosodic breaks. In order to write the rules a deep and careful analysis of the speech database and the voice talent’s specific pronunciation has been performed in addition to the study of Italian language’s properties, both from a phonetic and syntactic perspective. The evaluation of the new rules added to the system showed on improvement of 4.25% over our baseline. Finally this study shows the importance of the criteria used for the selection of the voice talent, revealing the significance of consistency in his/her performance of phonetic features for rule based text analysis components.