Abstract Automatic Speech Recognition (ASR) is a technology for identifying uttered word (s)
represented as an acoustic signal. However, one of the important aspects of a noise-robust …

We describe a novel extension of the Poisson regression model to be based on a multi-layer
perceptron, a type of neural network. This relaxes the assumptions of the traditional Poisson …

In this paper, through extension of the present methods and based on error minimization,
two fast and efficient layer-by-layer pre-training methods are proposed for initializing deep …

The performance drop of typical automatic speech recognition systems in real applications is
related to their not properly designed structure and training procedure. In this article, a …

Over the last decade, deep-learning methods have been gradually incorporated into
conventional automatic speech recognition (ASR) frameworks to create acoustic …

Here, formation of continuous attractor dynamics in a nonlinear recurrent neural network is
used to achieve a nonlinear speech denoising method, in order to implement robust …

Background: Cholera as an endemic disease remains a health issue in Iran despite
decrease in incidence. Since forecasting epidemic diseases provides appropriate …

Although the conventional wavelet transform possesses multi-resolution properties, it is not
optimized for speech recognition systems. It suffers from lower performance compared with …

In this article, for the purpose of improving neural network models applied in face recognition
using single image per person, a bidirectional neural network inspired of neocortex …

In this article, for the purpose of improving neural network models applied in face recognition
using single image per person, a bidirectional neural network inspired of neocortex …