Although supervised deep learning has revolutionized speech and audio processing, it has
necessitated the building of specialist models for individual tasks and application scenarios …

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 …

A key learning scenario in large-scale applications is that of federated learning, where a
centralized model is trained based on data originating from a large number of clients. We …

Reynolds, Douglas A., Quatieri, Thomas F., and Dunn, Robert B., Speaker Verification Using
Adapted Gaussian Mixture Models, Digital Signal Processing10 (2000), 19–41. In this paper …

Hidden Markov models—most often abbreviated to the acronym “HMMs”—are one of the
most successful statistical modelling ideas that have came up in the last forty years: the use …

A method of speaker adaptation for continuous density hidden Markov models (HMMs) is
presented. An initial speaker-independent system is adapted to improve the modelling of a …

This paper examines the application of linear transformations for speaker and environmental
adaptation in an HMM-based speech recognition system. In particular, transformations that …

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 …

While biometric authentication has advanced significantly in recent years, evidence shows
the technology can be susceptible to malicious spoofing attacks. The research community …

Successful speech perception requires that listeners map the acoustic signal to linguistic
categories. These map**s are not only probabilistic, but change depending on the …