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 …

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 …

A study of digital speech processing, synthesis and recognition. This second edition
contains new sections on the international standardization of robust and flexible speech …

A speaker-independent hidden Markov model (HMM) keyword recognizer (KWR) based on
a continuous-speech-recognition model is presented. The baseline keyword recognition …

A new speaker adaptation technique is proposed for improving speaker-independent
continuous speech recognition based on a decomposition of spectral variation sources. In …

Presents a maximum-likelihood (ML) stochastic matching approach to decrease the acoustic
mismatch between a test utterance and a given set of speech models so as to reduce the …

For the past two decades, research in speech recognition has been intensively carried out
worldwide, spurred on by advances in signal processing, algorithms, architectures, and …

An acoustic-class-dependent technique for text-independent speaker identification on very
short utterances is described. The technique is based on maximum-likelihood estimation of …

Recent advances in automatic speech recognition are accomplished by designing a plug-in
maximum a posteriori decision rule such that the forms of the acoustic and language model …