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20192025
most citedMultimodal Fusion with Deep Neural Networks for Audio-Video Emotion Recognition

43 citations · 72 across the 14 of their papers we have counts for

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7 papers · 1 filter

cs.SD2021

Towards Robust Speech-to-Text Adversarial Attack

Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich

This paper introduces a novel adversarial algorithm for attacking the state-of-the-art speech-to-text systems, namely DeepSpeech, Kaldi, and Lingvo. Our approach is based on develo…

cs.SD2021

Multi-Discriminator Sobolev Defense-GAN Against Adversarial Attacks for End-to-End Speech Systems

Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich

This paper introduces a defense approach against end-to-end adversarial attacks developed for cutting-edge speech-to-text systems. The proposed defense algorithm has four major ste…

cs.SD2021

Cyclic Defense GAN Against Speech Adversarial Attacks

Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich

This paper proposes a new defense approach for counteracting state-of-the-art white and black-box adversarial attack algorithms. Our approach fits into the implicit reactive defens…

cs.SD2020

Conditioning Trick for Training Stable GANs

Mohammad Esmaeilpour, Raymel Alfonso Sallo, Olivier St-Georges +2

In this paper we propose a conditioning trick, called difference departure from normality, applied on the generator network in response to instability issues during GAN training. W…

cs.SD2020

Class-Conditional Defense GAN Against End-to-End Speech Attacks

Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich

In this paper we propose a novel defense approach against end-to-end adversarial attacks developed to fool advanced speech-to-text systems such as DeepSpeech and Lingvo. Unlike con…

cs.SD2019

Speaker Sincerity Detection based on Covariance Feature Vectors and Ensemble Methods

Mohammed Senoussaoui, Patrick Cardinal, Najim Dehak +1

Automatic measuring of speaker sincerity degree is a novel research problem in computational paralinguistics. This paper proposes covariance-based feature vectors to model speech a…