Text-To-Speech Conversion with Neural Networks: A Recurrent TDNN Approach

Details Text-To-Speech Conversion with Neural Networks: A Recurrent TDNN Approach Text-To-Speech Conversion with Neural Networks: A Recurrent TDNN Approach

1998-11-24

arxiv.org/abs/cs/9811032v1

Proceedings of Eurospeech (1997) 561-564. Rhodes, Greece

Computer Science

Neural and Evolutionary Computing

4 pages, PostScript

Scientific paper

This paper describes the design of a neural network that performs the phonetic-to-acoustic mapping in a speech synthesis system. The use of a time-domain neural network architecture limits discontinuities that occur at phone boundaries. Recurrent data input also helps smooth the output parameter tracks. Independent testing has demonstrated that the voice quality produced by this system compares favorably with speech from existing commercial text-to-speech systems.

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