Introduction A successful speech recognition system has to determine features not only present in the input pattern at one point in time, but also features of input pattern changing over time ( e.g., Berthold, 1994; Benyettou, 1995). In network design, great importance must be attributed to correct choice of the number of hidden neurons, which helps avoiding problems of overfitting and contribu...

The reduction of maintenance costs through the use of condition based maintenance practices have become a primary goal of industrial maintenance managers. Systems that can monitor the calibration of sensors can help maintenance managers meet this goal. Recently, the use of autoassociative neural networks (AANNs) to perform on-line calibration monitoring of process sensors has been shown to be n...

We propose to use the Gamma filter [1] as a feature extractor for the preprocessing of speech signals. Gamma filter which can be implemented as a cascade of identical first order lowpass filters generates at its taps the Poisson Moments of an input signal. These moments carry spectral information about the recent history of the input signal. They can be used to construct time-frequency represen...

Discriminative training techniques define state-of-the-art performance for automatic speech recognition systems. However, they are inherently prone to overfitting, leading poor generalization when using limited data. In order address this issue, paper presents a full Bayesian framework account model uncertainty in sequence discriminative of factored TDNN acoustic models. Several learning based ...

We have previously introduced the Gamma MLP which is defined as an MLP with the usual synaptic weights replaced by gamma filters and associated gain terms throughout all layers. In this paper we apply the Gamma MLP to a larger scale speech phoneme recognition problem, analyze the operation of the network, and investigate why the Gamma MLP can perform better than alternatives. The Gamma MLP is c...

Speech recognition systems (SRS) designed for applications in low cost products like telephones or in systems with energetic constraints like autonomous vehicles are faced with the demand for solutions with low complexity. A small vocabulary consisting of a few command words as well as the digits is suucient for most of the applications but has to be recognized robustly. Here we report about in...

This research presents an improved automatic isolated-word recognition system for the Arabic sign language (ArSL) for the Jordanian accent. Our proposed system requires that the signer wears two gloves with different colors, he also should wear another colored mark on his head, this mark should have different color than the colors used in the gloves. In this paper the video for each sign is con...

This letter presents a technique for suppressing the effect of any type of impulsive noise in the context of Automatic Speech Recognition (ASR). The present study suggests the interposition in the Mel Frequency Cepstral Coefficients (MFCC) feature extraction front-end of a) an identification stage responsible for the detection of corrupted cepstral vectors and b) a restoration stage that acts l...