Duration prediction using multiple Gaussian process experts for GPR-based speech synthesis

Abstract

This paper proposes an alternative multi-level approach to duration prediction for improving prosody generation in statistical parametric speech synthesis using multiple Gaussian process experts. We use two duration models at different levels, specifically, syllable and phone. First, we individually train syllable- and phone-level duration models. Then, the predictive distributions of syllable and phone duration models are combined by product of Gaussians. The means of combined predictive distributions are used as predicted durations for synthetic speech. We show objective and subjective evaluation results for the proposed technique by comparing with the conventional ones when the techniques are applied to Gaussian process regression (GPR)-based speech synthesis.