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20192024
most citedMuSe 2020 -- The First International Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop

5 citations · 16 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.SD2023

HEAR4Health: A blueprint for making computer audition a staple of modern healthcare

Andreas Triantafyllopoulos, Alexander Kathan, Alice Baird +20

Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalen…

cs.SD2022★ 1 cited

The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes

Björn W. Schuller, Anton Batliner, Shahin Amiriparian +12

The ACM Multimedia 2022 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the…

cs.SD2022★ 3 cited

Continuous-Time Audiovisual Fusion with Recurrence vs. Attention for In-The-Wild Affect Recognition

Vincent Karas, Mani Kumar Tellamekala, Adria Mallol-Ragolta +2

In this paper, we present our submission to 3rd Affective Behavior Analysis in-the-wild (ABAW) challenge. Learningcomplex interactions among multimodal sequences is critical to rec…

cs.SD2022★ 1 cited

Audio Self-supervised Learning: A Survey

Shuo Liu, Adria Mallol-Ragolta, Emilia Parada-Cabeleiro +5

Inspired by the humans' cognitive ability to generalise knowledge and skills, Self-Supervised Learning (SSL) targets at discovering general representations from large-scale data wi…

cs.SD2021

EIHW-MTG: Second DiCOVA Challenge System Report

Adria Mallol-Ragolta, Helena Cuesta, Emilia Gómez +1

This work presents an outer product-based approach to fuse the embedded representations generated from the spectrograms of cough, breath, and speech samples for the automatic detec…

cs.SD2021

EIHW-MTG DiCOVA 2021 Challenge System Report

Adria Mallol-Ragolta, Helena Cuesta, Emilia Gómez +1

This paper aims to automatically detect COVID-19 patients by analysing the acoustic information embedded in coughs. COVID-19 affects the respiratory system, and, consequently, resp…