Identifying a person by his or her voice is an important human trait most take for granted in
natural human-to-human interaction/communication. Speaking to someone over the …

New waves of consumer-centric applications, such as voice search and voice interaction
with mobile devices and home entertainment systems, increasingly require automatic …

Automatic Speech Recognition (ASR) has historically been a driving force behind many
machine learning (ML) techniques, including the ubiquitously used hidden Markov model …

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 …

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 …

This paper presents the main paradigms for speaker identification, and recent work on
missing data methods to increase robustness. The feature extraction, speaker modeling and …

We derive an exact solution to the problem of maximum likelihood estimation of the
supervector covariance matrix used in extended MAP (or EMAP) speaker adaptation and …

We present a structured overview of adaptation algorithms for neural network-based speech
recognition, considering both hybrid hidden Markov model/neural network systems and end …

We describe a new approach to speech recognition, in which all Hidden Markov Model
(HMM) states share the same Gaussian Mixture Model (GMM) structure with the same …

A complete overview of distant automatic speech recognition The performance of
conventional Automatic Speech Recognition (ASR) systems degrades dramatically as soon …