Model Adaptation Approach to Speech Synthesis with Diverse Voices and Styles

In human computer interaction and dialogue systems, it is often desirable for text-to-speech synthesis to be able to generate natural sounding speech with an arbitrary speaker´s voice and with varying speaking styles and/or emotional expressions. We have developed an average-voice-based speech synthesis method using statistical average voice models and model adaptation techniques for this purpose. In this paper, we describe an overview of the speech synthesis system and show the current performance with several experimental results.