A continuous vocoder for statistical parametric speech synthesis and its evaluation using an audio-visual phonetically annotated Arabic corpus

In this paper, we present an extension of a novel continuous residual-based vocoder for statistical parametric speech synthesis by addressing two objectives. First, because the noise component is often not accurately modelled in modern vocoders (e.g. STRAIGHT), a new technique for modelling unvoiced sounds is proposed by adding time domain envelope to the unvoiced segments to avoid any residual buzziness. Four time-domain envelopes (Amplitude, Hilbert, Triangular and True) are investigated, enhanced, and then applied to the noise component of the excitation in our continuous vocoder, i.e. of which all parameters are continuous. With the future aim of producing high-quality Arabic speech synthesis, we secondly apply this vocoder on a modern standard Arabic audio-visual corpus which is annotated both phonetically and visually, and dedicated to emotional speech processing studies. In an objective experiment, we investigated the Phase Distortion Deviation, whereas a MUSHRA type subjective listening test was conducted comparing natural and vocoded speech samples. As a result, both experiments based on the proposed noise modelling have shown satisfactory results in terms of naturalness and intelligibility, while outperforming STRAIGHT and other earlier residual-based approaches. (C) 2019 Elsevier Ltd. All rights reserved.