Paper: Generating Synthetic Speech Prosody With Lazy Learning In Tree Structures

ACL ID W00-0716
Title Generating Synthetic Speech Prosody With Lazy Learning In Tree Structures
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2000
Authors

We present ongoing work on prosody predic- tion for speech synthesis. This approach con- siders sentences as tree structures and infers the prosody from a corpus of such structures using machine learning techniques. The predic- tion is achieved from the prosody of the closest sentence of the corpus through tree similarity measurements, using either the nearest neigh- bour algorithm or an analogy-based approach. We introduce two different tree structure rep- resentations, the tree similarity metrics consid- ered, and then we discuss the different predic- tion methods. Experiments are currently under process to qualify this approach.