Unit selection for speech synthesis based on acoustic criteria

Abstract

This paper presents a new approach to unit selection for corpus-based speech synthesis, in which the units are selected according to acoustic criteria. In a training stage, an acoustic clustering is carried out using context dependent HMMs. In the synthesis stage, an acoustic target is generated and divided into segments corresponding to the required unit sequence. Then, the acoustic unit sequence that best matches the target is selected. Tests are carried out which show the relevance of the proposed method. © Springer-Verlag Berlin Heidelberg 2005.