This paper proposes a new text-to-speech (TTS) system that utilizes large numbers of speech segments to produce very natural and intelligible synthetic speech. There are two innovations; new multiform synthesis units and a new speech modification algorithm based on a vocoder that offers harmonics reconstruction. The multiform units make it possible to reduce acoustic discontinuities at concatenation points and unnatural sound by preparing synthesis units with various lengths and various F/sub 0/ contours. The new speech modification algorithm, on the other hand, improves the quality of prosody modified speech. This algorithm is extremely effective in synthesizing speech whose prosodic parameters are quite different from those of synthesis units. Listening tests confirm that the new synthesis units yield speech with high intelligibility and naturalness, and that the new speech modification algorithm is superior to all other conventional vocoders and waveform domain algorithms including TD-PSOLA, especially when modifying the F/sub 0/ frequency upward.

In this paper, we first introduce the use of Gaussian mixture models (GMM) for Chinese tone classification in continuous speech. Then, we explain how to integrate it with the HMM-based speech recognition system. Finally, we provide the tone classification accuracy of this probabilistic method which is tested with Chinese continuous speech database of national “863” project.

This paper proposes a new speech modification algorithm which makes it possible to change the fundamental frequency (F/sub 0/) while preserving high quality. One novel point of the algorithm is that the spectrum envelope is transformed according to amount of F/sub 0/ modification. Based on a codebook mapping formulation, transformation rules are generated using speech data uttered in a different F/sub 0/ range. The rules have two purposes: one is transforming the spectrum envelope of the low frequency band and the other is adjusting the balance between low band power and high band power. The proposed algorithm is applied to a text-to-speech system based on waveform concatenation, and good performance is confirmed by listening tests.