Nowadays speech synthesis or text to speech (TTS), an ability of system to produce human
like natural sounding voice from the written text, is gaining popularity in the field of speech …

This review gives a general overview of techniques used in statistical parametric speech
synthesis. One instance of these techniques, called hidden Markov model (HMM)-based …

Conventional approaches to statistical parametric speech synthesis typically use decision
tree-clustered context-dependent hidden Markov models (HMMs) to represent probability …

Hidden Markov models (HMMs) and Gaussian mixture models (GMMs) are the two most
common types of acoustic models used in statistical parametric approaches for generating …

This paper gives a general overview of hidden Markov model (HMM)-based speech
synthesis, which has recently been demonstrated to be very effective in synthesizing …

A statistical parametric speech synthesis system based on hidden Markov models (HMMs)
has grown in popularity over the last few years. This system simultaneouslymodels …

Statistical parametric speech synthesis (SPSS) using deep neural networks (DNNs) has
shown its potential to produce naturally-sounding synthesized speech. However, there are …

In this paper, we evaluate the vulnerability of speaker verification (SV) systems to synthetic
speech. The SV systems are based on either the Gaussian mixture model–universal …

In this paper, we analyze the effects of several factors and configuration choices
encountered during training and model construction when we want to obtain better and …

This paper describes an hidden Markov model (HMM)-based speech synthesizer that
utilizes glottal inverse filtering for generating natural sounding synthetic speech. In the …