In this paper, methodologies for effective speech recognition are considered along with
evaluations of an NRL speech in noise corpus entitled SPINE. When speech is produced in …

The field of automatic speech recognition has evolved greatly since the introduction of deep
learning, which began only about 5 years ago. In particular, as more and more products …

The recently introduced second CHiME challenge is a difficult two-microphone speech
recognition task with non-stationary interference. Current approaches in the source …

Speech recognition systems need to operate in a wide range of conditions. Thus they should
be robust to extrinsic variability caused by various acoustic factors, for example speaker …

The issue of noise robustness in automatic speech recognition is of practical importance and
largely unsolved. In this thesis, this problem is tackled from both perspectives of front-end …

Automatic speech recognition (ASR) systems are finding increasing use in everyday life.
Many of the commonplace environments where the systems are used are noisy, for example …

This thesis details the development of a model-based noise compensation technique,
Parallel Model Combination (PMC). The aim of PMC is to alter the parameters of a set of …

Recent advances in robust speech recognition technology Page 1 ISBN: 978-1-60805-172-4
Recent Advances in Robust Speech Recognition Technology 10 5 0 0 1 2 3 4 5 6 7 8 9 ӨӨ …

This paper presents a multiple-model framework for noiserobust speech recognition. In this
framework, multiple HMM model sets are trained-each identified by a noise type and a …

Over the years, the focus in noise robust speech recognition has shifted from noise robust
features to model based techniques such as parallel model combination and uncertainty …