Real-time frequency-based noise-robust Automatic Speech Recognition using Multi-Nets Artificial Neural Networks: A multi-views multi-learners approach
SR Shahamiri, SSB Salim - Neurocomputing, 2014 - Elsevier
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 …
represented as an acoustic signal. However, one of the important aspects of a noise-robust …
Nonlinear Poisson regression using neural networks: a simulation study
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 …
perceptron, a type of neural network. This relaxes the assumptions of the traditional Poisson …
A fast and efficient pre-training method based on layer-by-layer maximum discrimination for deep neural networks
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 …
two fast and efficient layer-by-layer pre-training methods are proposed for initializing deep …
Toward growing modular deep neural networks for continuous speech recognition
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 …
related to their not properly designed structure and training procedure. In this article, a …
Heterogeneous reservoir computing models for persian speech recognition
Over the last decade, deep-learning methods have been gradually incorporated into
conventional automatic speech recognition (ASR) frameworks to create acoustic …
conventional automatic speech recognition (ASR) frameworks to create acoustic …
Nonlinear enhancement of noisy speech, using continuous attractor dynamics formed in recurrent neural networks
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 …
used to achieve a nonlinear speech denoising method, in order to implement robust …
[HTML][HTML] Model of cholera forecasting using artificial neural network in Chabahar City, Iran
Z Pezeshki, M Tafazzoli-Shadpour… - International Journal of …, 2016 - lup.lub.lu.se
Background: Cholera as an endemic disease remains a health issue in Iran despite
decrease in incidence. Since forecasting epidemic diseases provides appropriate …
decrease in incidence. Since forecasting epidemic diseases provides appropriate …
A new representation for speech frame recognition based on redundant wavelet filter banks
Although the conventional wavelet transform possesses multi-resolution properties, it is not
optimized for speech recognition systems. It suffers from lower performance compared with …
optimized for speech recognition systems. It suffers from lower performance compared with …
Improving face recognition from a single image per person via virtual images produced by a bidirectional network
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 …
using single image per person, a bidirectional neural network inspired of neocortex …
Improving pose manifold and virtual images using bidirectional neural networks in face recognition using single image per person
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 …
using single image per person, a bidirectional neural network inspired of neocortex …