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 …

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 …

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

We introduce a simple and effective deep learning approach to automatically generate
natural looking speech animation that synchronizes to input speech. Our approach uses a …

This paper derives a speech parameter generation algorithm for HMM-based speech
synthesis, in which the speech parameter sequence is generated from HMMs whose …

In this paper, we describe an HMM-based speech synthesis system in which spectrum, pitch
and state duration are modeled simultaneously in a unified framework of HMM. In the …

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 …

Disclosed are apparatus and methods for processing spoken speech. Input speech can be
received at a computing system. During a first pass of speech recognition, a plurality of …

This paper proposes a new kind of hidden Markov model (HMM) based on multi-space
probability distribution, and derives a parameter estimation algorithm for the extended HMM …

A statistical speech synthesis system based on the hidden Markov model (HMM) was
recently proposed. In this system, spectrum, excitation, and duration of speech are modeled …