Search Results for author: Adria Mallol-Ragolta

Found 7 papers, 1 papers with code

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

no code implementations13 May 2022 Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Christian Bergler, Maurice Gerczuk, Natalie Holz, Pauline Larrouy-Maestri, Sebastian P. Bayerl, Korbinian Riedhammer, Adria Mallol-Ragolta, Maria Pateraki, Harry Coppock, Ivan Kiskin, Marianne Sinka, Stephen Roberts

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 Vocalisations and Stuttering Sub-Challenges, a classification on human non-verbal vocalisations and speech has to be made; the Activity Sub-Challenge aims at beyond-audio human activity recognition from smartwatch sensor data; and in the Mosquitoes Sub-Challenge, mosquitoes need to be detected.

Human Activity Recognition

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

no code implementations24 Mar 2022 Vincent Karas, Mani Kumar Tellamekala, Adria Mallol-Ragolta, Michel Valstar, Björn W. Schuller

To clearly understand the performance differences between recurrent and attention models in audiovisual affect recognition, we present a comprehensive evaluation of fusion models based on LSTM-RNNs, self-attention and cross-modal attention, trained for valence and arousal estimation.

Arousal Estimation Multimodal Emotion Recognition

Audio Self-supervised Learning: A Survey

no code implementations2 Mar 2022 Shuo Liu, Adria Mallol-Ragolta, Emilia Parada-Cabeleiro, Kun Qian, Xin Jing, Alexander Kathan, Bin Hu, Bjoern W. Schuller

Inspired by the humans' cognitive ability to generalise knowledge and skills, Self-Supervised Learning (SSL) targets at discovering general representations from large-scale data without requiring human annotations, which is an expensive and time consuming task.

Self-Supervised Learning

EIHW-MTG DiCOVA 2021 Challenge System Report

no code implementations13 Oct 2021 Adria Mallol-Ragolta, Helena Cuesta, Emilia Gómez, Björn W. Schuller

This paper aims to automatically detect COVID-19 patients by analysing the acoustic information embedded in coughs.

MuSe 2020 -- The First International Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop

1 code implementation30 Apr 2020 Lukas Stappen, Alice Baird, Georgios Rizos, Panagiotis Tzirakis, Xinchen Du, Felix Hafner, Lea Schumann, Adria Mallol-Ragolta, Björn W. Schuller, Iulia Lefter, Erik Cambria, Ioannis Kompatsiaris

Multimodal Sentiment Analysis in Real-life Media (MuSe) 2020 is a Challenge-based Workshop focusing on the tasks of sentiment recognition, as well as emotion-target engagement and trustworthiness detection by means of more comprehensively integrating the audio-visual and language modalities.

Emotion Recognition Multimodal Sentiment Analysis

Adversarial-based neural networks for affect estimations in the wild

no code implementations3 Feb 2020 Decky Aspandi, Adria Mallol-Ragolta, Björn Schuller, Xavier Binefa

However, the use of latent features, which is feasible through adversarial learning, is not largely explored, yet.

AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition

no code implementations10 Jul 2019 Fabien Ringeval, Björn Schuller, Michel Valstar, NIcholas Cummins, Roddy Cowie, Leili Tavabi, Maximilian Schmitt, Sina Alisamir, Shahin Amiriparian, Eva-Maria Messner, Siyang Song, Shuo Liu, Ziping Zhao, Adria Mallol-Ragolta, Zhao Ren, Mohammad Soleymani, Maja Pantic

The Audio/Visual Emotion Challenge and Workshop (AVEC 2019) "State-of-Mind, Detecting Depression with AI, and Cross-cultural Affect Recognition" is the ninth competition event aimed at the comparison of multimedia processing and machine learning methods for automatic audiovisual health and emotion analysis, with all participants competing strictly under the same conditions.

Emotion Recognition

Cannot find the paper you are looking for? You can Submit a new open access paper.