no code implementations • 18 Apr 2024 • Shahin Amiriparian, Maurice Gerczuk, Justina Lutz, Wolfgang Strube, Irina Papazova, Alkomiet Hasan, Alexander Kathan, Björn W. Schuller
The metadata integration yields a balanced accuracy of $94. 4\,\%$, marking an absolute improvement of $28. 2\,\%$, demonstrating the efficacy of our proposed approaches for automatic suicide risk assessment in emergency medicine.
no code implementations • 16 May 2023 • Niklas Mueller, Steffen Klug, Andreas Koenig, Alexander Kathan, Lukas Christ, Bjoern Schuller, Shahin Amiriparian
Integrating research on laughter, affect-as-information, and infomediaries' social evaluations of firms, we hypothesize that voiced laughter in executive communication positively affects social approval, defined as audience perceptions of affinity towards an organization.
1 code implementation • 5 May 2023 • Lukas Christ, Shahin Amiriparian, Alice Baird, Alexander Kathan, Niklas Müller, Steffen Klug, Chris Gagne, Panagiotis Tzirakis, Eva-Maria Meßner, Andreas König, Alan Cowen, Erik Cambria, Björn W. Schuller
Participants predict the presence of spontaneous humour in a cross-cultural setting.
no code implementations • 28 Apr 2023 • Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Alexander Barnhill, Maurice Gerczuk, Andreas Triantafyllopoulos, Alice Baird, Panagiotis Tzirakis, Chris Gagne, Alan S. Cowen, Nikola Lackovic, Marie-José Caraty, Claude Montacié
The ACM Multimedia 2023 Computational Paralinguistics Challenge addresses two different problems for the first time in a research competition under well-defined conditions: In the Emotion Share Sub-Challenge, a regression on speech has to be made; and in the Requests Sub-Challenges, requests and complaints need to be detected.
no code implementations • 31 Dec 2022 • Björn W. Schuller, Shahin Amiriparian, Anton Batliner, Alexander Gebhard, Maurice Gerzcuk, Vincent Karas, Alexander Kathan, Lennart Seizer, Johanna Löchner
We then name exemplary use cases of computational charismatic skills before switching to ethical aspects and concluding this overview and perspective on building charisma-enabled AI.
1 code implementation • 21 Dec 2022 • Lukas Christ, Shahin Amiriparian, Manuel Milling, Ilhan Aslan, Björn W. Schuller
Telling stories is an integral part of human communication which can evoke emotions and influence the affective states of the audience.
1 code implementation • 20 Dec 2022 • Daniel Lukas Rothenpieler, Shahin Amiriparian
Using our BMHRL, we show the suitability of the HRL agent in the generation of content-complete and grammatically sound sentences by achieving $4. 91$, $2. 23$, and $10. 80$ in BLEU3, BLEU4, and METEOR scores, respectively on the ActivityNet Captions dataset.
1 code implementation • 28 Sep 2022 • Lukas Christ, Shahin Amiriparian, Alexander Kathan, Niklas Müller, Andreas König, Björn W. Schuller
Our findings suggest that for the automatic analysis of humour and its sentiment, facial expressions are most promising, while humour direction can be best modelled via text-based features.
1 code implementation • 23 Jun 2022 • Lukas Christ, Shahin Amiriparian, Alice Baird, Panagiotis Tzirakis, Alexander Kathan, Niklas Müller, Lukas Stappen, Eva-Maria Meßner, Andreas König, Alan Cowen, Erik Cambria, Björn W. Schuller
For this year's challenge, we feature three datasets: (i) the Passau Spontaneous Football Coach Humor (Passau-SFCH) dataset that contains audio-visual recordings of German football coaches, labelled for the presence of humour; (ii) the Hume-Reaction dataset in which reactions of individuals to emotional stimuli have been annotated with respect to seven emotional expression intensities, and (iii) the Ulm-Trier Social Stress Test (Ulm-TSST) dataset comprising of audio-visual data labelled with continuous emotion values (arousal and valence) of people in stressful dispositions.
no code implementations • 12 Jun 2022 • Mani Kumar Tellamekala, Shahin Amiriparian, Björn W. Schuller, Elisabeth André, Timo Giesbrecht, Michel Valstar
In particular, we impose Calibration and Ordinal Ranking constraints on the variance vectors of audiovisual latent distributions.
no code implementations • 13 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.
no code implementations • 9 May 2022 • Andreas Triantafyllopoulos, Sandra Ottl, Alexander Gebhard, Esther Rituerto-González, Mirko Jaumann, Steffen Hüttner, Valerie Dieter, Patrick Schneeweiß, Inga Krauß, Maurice Gerczuk, Shahin Amiriparian, Björn W. Schuller
Although running is a common leisure activity and a core training regiment for several athletes, between $29\%$ and $79\%$ of runners sustain an overuse injury each year.
no code implementations • 17 Feb 2022 • Harry Coppock, Alican Akman, Christian Bergler, Maurice Gerczuk, Chloë Brown, Jagmohan Chauhan, Andreas Grammenos, Apinan Hasthanasombat, Dimitris Spathis, Tong Xia, Pietro Cicuta, Jing Han, Shahin Amiriparian, Alice Baird, Lukas Stappen, Sandra Ottl, Panagiotis Tzirakis, Anton Batliner, Cecilia Mascolo, Björn W. Schuller
The COVID-19 pandemic has caused massive humanitarian and economic damage.
1 code implementation • 26 Sep 2021 • Yasaman Boreshban, Seyed Morteza Mirbostani, Gholamreza Ghassem-Sani, Seyed Abolghasem Mirroshandel, Shahin Amiriparian
Contemporary question answering (QA) systems, including transformer-based architectures, suffer from increasing computational and model complexity which render them inefficient for real-world applications with limited resources.
1 code implementation • 16 Sep 2021 • Sandra Ottl, Shahin Amiriparian, Maurice Gerczuk, Björn Schuller
Finally, a linear SVR is trained on this feature representation.
1 code implementation • 23 Apr 2021 • Shahin Amiriparian, Tobias Hübner, Maurice Gerczuk, Sandra Ottl, Björn W. Schuller
By obtaining state-of-the-art results on a set of paralinguistics tasks, we demonstrate the suitability of the proposed transfer learning approach for embedded audio signal processing, even when data is scarce.
no code implementations • 20 Apr 2021 • Shahin Amiriparian, Artem Sokolov, Ilhan Aslan, Lukas Christ, Maurice Gerczuk, Tobias Hübner, Dmitry Lamanov, Manuel Milling, Sandra Ottl, Ilya Poduremennykh, Evgeniy Shuranov, Björn W. Schuller
Text encodings from automatic speech recognition (ASR) transcripts and audio representations have shown promise in speech emotion recognition (SER) ever since.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
1 code implementation • 10 Mar 2021 • Maurice Gerczuk, Shahin Amiriparian, Sandra Ottl, Björn Schuller
The corpus is then utilised to create a novel framework for multi-corpus speech emotion recognition, namely EmoNet.
no code implementations • 24 Feb 2021 • Björn W. Schuller, Anton Batliner, Christian Bergler, Cecilia Mascolo, Jing Han, Iulia Lefter, Heysem Kaya, Shahin Amiriparian, Alice Baird, Lukas Stappen, Sandra Ottl, Maurice Gerczuk, Panagiotis Tzirakis, Chloë Brown, Jagmohan Chauhan, Andreas Grammenos, Apinan Hasthanasombat, Dimitris Spathis, Tong Xia, Pietro Cicuta, Leon J. M. Rothkrantz, Joeri Zwerts, Jelle Treep, Casper Kaandorp
The INTERSPEECH 2021 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the COVID-19 Cough and COVID-19 Speech Sub-Challenges, a binary classification on COVID-19 infection has to be made based on coughing sounds and speech; in the Escalation SubChallenge, a three-way assessment of the level of escalation in a dialogue is featured; and in the Primates Sub-Challenge, four species vs background need to be classified.
no code implementations • 17 Dec 2020 • Katrin D. Bartl-Pokorny, Florian B. Pokorny, Anton Batliner, Shahin Amiriparian, Anastasia Semertzidou, Florian Eyben, Elena Kramer, Florian Schmidt, Rainer Schönweiler, Markus Wehler, Björn W. Schuller
Group differences in the front vowels /i:/ and /e:/ are additionally reflected in the variation of the fundamental frequency and the harmonics-to-noise ratio, group differences in back vowels /o:/ and /u:/ in statistics of the Mel-frequency cepstral coefficients and the spectral slope.
1 code implementation • 15 May 2020 • Shahin Amiriparian, Pawel Winokurow, Vincent Karas, Sandra Ottl, Maurice Gerczuk, Björn W. Schuller
On the development partition of the data, we achieve Spearman's correlation coefficients of . 324, . 283, and . 320 with the targets on the Karolinska Sleepiness Scale by utilising attention and non-attention autoencoders, and the fusion of both autoencoders' representations, respectively.
no code implementations • 10 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.
1 code implementation • 12 Dec 2017 • Michael Freitag, Shahin Amiriparian, Sergey Pugachevskiy, NIcholas Cummins, Björn Schuller
auDeep is a Python toolkit for deep unsupervised representation learning from acoustic data.
Sound Audio and Speech Processing