Detecting damage at an early stage can avoid a serious catastrophic failure of structures
due to inevitable cause, such as fatigue, environmental corrosion, and natural disasters …

The presented paper introduces principal component analysis application for dimensionality
reduction of variables describing speech signal and applicability of obtained results for the …

Speech signal gets contaminated by background noise affecting its quality and intelligibility.
There are different sources of additive noise. This additive noise, either stationary or non …

Voice is perceived as a form of biometrics which communicates valuable and rich
information pertinent to an individual, such as his or her identity, gender, accent, age and …

A comparative evaluation of speech enhancement algorithms for robust automatic speech
recognition is presented. The evaluation is performed on a core test set of the TIMIT speech …

In this paper, we proposed speech enhancement method using principal component
analysis (PCA) for noisy signal. This algorithm is based on the PCA which is subspace …

In this study, we focus on the issue of noise distortion in speech signals, and develop two
novel unsupervised speech enhancement algorithms including temporal lowpass filtering …

This paper presents a system that allows the user to interact by speech with a Radio-
Frequency IDentification (RFID) network working in a highly noisy environment. A new …

Abstract The Common Vector Approach (CVA) is a subspace classifier with significant
success in isolated word recognition. However, when sufficient data is available, mixing the …

Confusion matrices have been widely used to increase the accuracy of speech recognisers,
but usually a mean confusion matrix, averaged over many speakers, is used. However …