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

Many alternative models have been proposed to address some of the shortcomings of the
hidden Markov model (HMM), which is currently the most popular approach to speech …

The accuracy of speech recognition systems degrades severely when the systems are
operated in adverse acoustical environments. In recent years many approaches have been …

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 …

From many decades, people are working research in the area of voice recognition and
communication. Researchers have valuable contribution in this area up to now. They have …

This paper investigates the relative sensitivity of a Gaussian mixture model (GMM) based
voice verification algorithm to computer voice-altered imposters. First, a new trainable …

“Segmental hidden Markov models”(SHMMs) are intended to overcome important speech-
modelling limitations of the conventional-HMM approach by representing sequences (or …

Phonetic recognition is provided by capturing dynamical behavior and statistical
dependencies of the acoustic attributes used to represent a subject speech waveform. A …

This paper introduces a novel time-domain approach to modeling and classifying speech
phoneme waveforms. The approach is based on statistical models of reconstructed phase …

This paper shows that the HMM whose state output vector includes static and dynamic
feature parameters can be reformulated as a trajectory model by imposing the explicit …