Major progress is being recorded regularly on both the technology and exploitation of
automatic speech recognition (ASR) and spoken language systems. However, there are still …

The performance levels of most current speech recognizers degrade significantly when
environmental noise occurs during use. Such performance degradation is mainly caused by …

The use of hidden Markov models for speech recognition has become predominant in the
last several years, as evidenced by the number of published papers and talks at major …

In this paper, a framework for maximum a posteriori (MAP) estimation of hidden Markov
models (HMM) is presented. Three key issues of MAP estimation, namely, the choice of prior …

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 …

Considerable progress has been made in speech-recognition technology over the last few
years and nowhere has this progress been more evident than in the area of large …

This paper describes a new model-based speaker adaptation algorithm called the
eigenvoice approach. The approach constrains the adapted model to be a linear …

A trend in automatic speech recognition systems is the use of continuous mixture-density
hidden Markov models (HMMs). Despite the good recognition performance that these …

In an effort to reduce the degradation in speech recognition performance caused by
variation in vocal tract shape among speakers, a frequency warping approach to speaker …

In spite of the advances accomplished throughout the last decades, automatic speech
recognition (ASR) is still a challenging and difficult task. In particular, recognition systems …