4 accepted papers
In this paper, we present an expressive visual text to speech system (VTTS) based on a deep neural network (DNN). Given an input text sentence and a set of expression tags, the VTTS is able to produce not only the audio speech, but also the accompanying facial movements. The expressions can either b…
This paper presents a method to iteratively estimate phase information from speech in the cepstrum domain. It assumes that correct markings of pitch periods, which may not correspond to glottal closure instants (GCI), are available and can be used to extract the smooth spectral envelope of speech. B…
In statistical parametric speech synthesis such as Hidden Markov Model (HMM) based synthesis, one of the problems is in the over-smoothing of parameters, which leads to a muffled sensation in the synthesised output. In this paper, we propose an approach in which the high frequency spectrum is modell…
Sinusoidal vocoders can generate high quality speech, but they have not been extensively applied to statistical parametric speech synthesis. This paper presents two ways for using dynamic sinusoidal models for statistical speech synthesis, enabling the sinusoid parameters to be modelled in HMM-based…