24 citations · 49 across the 8 of their papers we have counts for
8 papers
Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework
Mohammad Khalooei, Mohammad Mehdi Homayounpour, Maryam Amirmazlaghani
Deep neural network models are used today in various applications of artificial intelligence, the strengthening of which, in the face of adversarial attacks is of particular import…
Efficient Attention Branch Network with Combined Loss Function for Automatic Speaker Verification Spoof Detection
Amir Mohammad Rostami, Mohammad Mehdi Homayounpour, Ahmad Nickabadi
Many endeavors have sought to develop countermeasure techniques as enhancements on Automatic Speaker Verification (ASV) systems, in order to make them more robust against spoof att…
Feature Joint-State Posterior Estimation in Factorial Speech Processing Models using Deep Neural Networks
Mahdi Khademian, Mohammad Mehdi Homayounpour
This paper proposes a new method for calculating joint-state posteriors of mixed-audio features using deep neural networks to be used in factorial speech processing models. The joi…
Neural Machine Translation on Scarce-Resource Condition: A case-study on Persian-English
Mohaddeseh Bastan, Shahram Khadivi, Mohammad Mehdi Homayounpour
Neural Machine Translation (NMT) is a new approach for Machine Translation (MT), and due to its success, it has absorbed the attention of many researchers in the field. In this pap…
Monaural Multi-Talker Speech Recognition using Factorial Speech Processing Models
Mahdi Khademian, Mohammad Mehdi Homayounpour
A Pascal challenge entitled monaural multi-talker speech recognition was developed, targeting the problem of robust automatic speech recognition against speech like noises which si…
Modeling State-Conditional Observation Distribution using Weighted Stereo Samples for Factorial Speech Processing Models
Mahdi Khademian, Mohammad Mehdi Homayounpour
This paper investigates the effectiveness of factorial speech processing models in noise-robust automatic speech recognition tasks. For this purpose, the paper proposes an idealist…
Deep Belief Network Training Improvement Using Elite Samples Minimizing Free Energy
Mohammad Ali Keyvanrad, Mohammad Mehdi Homayounpour
Nowadays this is very popular to use deep architectures in machine learning. Deep Belief Networks (DBNs) are deep architectures that use stack of Restricted Boltzmann Machines (RBM…
A brief survey on deep belief networks and introducing a new object oriented toolbox (DeeBNet)
Mohammad Ali Keyvanrad, Mohammad Mehdi Homayounpour
Nowadays, this is very popular to use the deep architectures in machine learning. Deep Belief Networks (DBNs) are deep architectures that use stack of Restricted Boltzmann Machines…