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Learnable Phonetic Representations in a Connectionist TTS System — II: Phonetics to Speech

  • Andrew D. Cohen
Chapter
Part of the Telecommunications Technology & Applications Series book series (TTAP)

Abstract

In an earlier chapter, we described the overall structure of the SOMtalk text-to-speech system and detailed results suggesting that non-symbolic (‘phonetic’) representations — based on trajectories through a ‘phonetic’ space derived from a self-organising map — may play a useful part in deriving pronunciations from text. A similar strategy suggests itself for the subsequent stage in which synthetic speech is produced from the ‘phonetic’ representation. This makes it possible to bypass a symbolic ‘phonemic’ stage in the overall, trained system. In this case, only a small database has been used for learning because of the high computational cost of training on spectral data, but some encouraging preliminary results have been obtained.

Keywords

Dynamic Time Warping Speech Synthesis Multiple Network Natural Speech Unseen Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Andrew D. Cohen

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