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Alessandro Lameiras Koerich

5 accepted papers

2026

BAH Dataset for Ambivalence/Hesitancy Recognition in Videos for Behavioural Change

Manuela González-González, Soufiane Belharbi, Muhammad Osama Zeeshan, Masoumeh Sharafi, Muhammad Haseeb Aslam, Marco Pedersoli +3
ICLR 2026poster

This paper introduces the Behavioral Ambivalence/Hesitancy (BAH) dataset collected for the Ambivalence/Hesitancy (A/H) recognition task in videos. In particular, this task involves recognizing conflicting emotions linked to A/H from question-and-answer videos captured for behavior analysis. The data…

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2026

Personalized Feature Translation for Expression Recognition: An Efficient Source-Free Domain Adaptation Method

Masoumeh Sharafi, Soufiane Belharbi, Muhammad Osama Zeeshan, HOUSSEM Ben Salem, Ali Etemad, Alessandro Lameiras Koerich +3
ICLR 2026poster

Facial expression recognition (FER) models are employed in many video-based affective computing applications, such as human-computer interaction and healthcare monitoring. However, deep FER models often struggle with subtle expressions and high inter-subject variability, limiting their performance…

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2022

Towards Robust Speech-to-Text Adversarial Attack

Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
ICASSP 2022accepted

This paper introduces a novel adversarial algorithm for attacking the advanced speech-to-text transcription systems. Our proposed approach is based on developing an extension for the conventional distortion condition of the general adversarial optimization formulation using the Cramér integral proba…

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2021

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

Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
ICASSP 2021accepted

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 conventional defense approaches, the proposed approach does not directly employ low-level transformations such as autoencod…

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2020

Detection of Adversarial Attacks and Characterization of Adversarial Subspace

Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
ICASSP 2020accepted

Adversarial attacks have always been a serious threat for any data-driven model. In this paper, we explore subspaces of adversarial examples in unitary vector domain, and we propose a novel detector for defending our models trained for environmental sound classification. We measure chordal distance…

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