A new method of estimating the coefficients of an autoregressive (AR) model using real-
valued neural network (RVNN) technique is presented in this paper. The coefficients of the …

Recurrent neural networks (RNN) and feed-forward multi-layer perceptron's have been
proposed for determining the absence and presence of speech in continuous voice signals …

A nonlinear predictive model of speech, based on the method of time delay reconstruction, is
presented and approximated using a fully connected recurrent neural network (RNN) …

Feed-forward multi-layer perceptrons (MLP) and recurrent neural networks (RNN) fed with
different sets of acoustic features are proposed for computing the presence and absence of …

Abstract Voice Activity Detection (VAD) is considered as an important pre-processing step in
speech processing systems such as speech enhancement, speech recognition, gender and …

We propose a new robust recursive procedure based on the weighted recursive least
squares (WRLS) algorithm with variable forgetting factor (VFF) and frame-based quadratic …

This paper describes procedures to screening vocal diseases using acoustic speech data
which is collected from ARS (Automatic Response System). Speech data from normal …

A voice activity detection (VAD) algorithm using the radial basis function (RBF) network is
proposed. The k-means clustering and least mean square algorithms are used to update the …

In this letter, a robust voice activity detection (VAD) algorithm is presented. This proposed
VAD algorithm makes use of the perceptual wavelet-packet transform and the Teager …

This paper proposes a feature for voice activity detection (VAD) obtained from a speech
signal analysis that uses the exponential autoregressive (ExpAR) model. This model …