Speech Database Compacted for an Embedded Mandarin TTS System

Abstract

In recent years, the unit selection based concatenative speech synthesis system that uses large speech database has become popular because it can produce high quality synthesized speech. However, using such a large speech database is not practical for many applications such as those ported on embedded devices with the storage requirement and the computational complexity involved in searching it. In this paper, it proposed the context based pruning algorithm and waveform adjustment effect based pruning algorithm to compact the speech database. At last, it presents experimental results and discussion.