Structural Data-Driven Prosody Model for TTS Synthesis

This paper introduces a new data-driven prosody model for the text-to-speech system ARTIC. The model is intended to be almost language-independent and to generate naturally sounding intonation with a link to semantics. It is based on text parametrisation using a new prosodic grammar and on automatic speech corpora analysis methods. Its performance is evaluated by results of presented listening tests.