Science and Education Publishing Journal of Computer Sciences and Applications 2328-725X 1 1 2013 05 19 Prosodic Boundary Prediction for Greek Speech Synthesis 61 74 EN Panagiotis Zervas Department of Music Technology & Acoustics, Technological Educational Institute of Crete, Rethymnon Branch, Greece JCSA2013142 10.12691/jcsa-1-4-2 2012 12 30 2013 05 18 2013 05 19 In this article, we evaluate features and algorithms for the task of prosodic boundary prediction for Greek. For this purpose a prosodic corpus composed of generic domain text was constructed. Feature contribution was evaluated and ranked with the application of information gain ranking and correlation-based feature selection filtering methods. Resulted datasets were applied to C4.5 decision tree, one-neighbour instance based learner and Bayesian learning methods. Models performance exploitation led as to the construction of a practically optimal feature set whose prediction effectiveness was evaluated with two prosodic databases. In terms of total accuracy and F-measure, evaluation results established the decision tree effectiveness in learning rules for prosodic boundary prediction.