Prosody Prediction from Tree-like Structure Similarities

Authors:
Laurent Blin
Affiliations:
-
Venue:
TDS '00 Proceedings of the Third International Workshop on Text, Speech and Dialogue
Year:
2000

Citing 5
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Abstract

We present ongoing work on prosody prediction for speech synthesis. This approach considers sentences as tree-like structures and decides on the prosody from a corpus of such structures using machine learning techniques. The prediction is achieved from the prosody of the closest sentence of the corpus through tree similarity measurements in a nearest neighbour context. We introduce a syntactic structure and a performance structure representation, the tree similarity metrics considered, and then we discuss the prediction method. Experiments are currently under process to qualify this approach.