no code implementations • 30 Apr 2024 • Andreas Triantafyllopoulos, Björn W. Schuller
Imbuing machines with the ability to talk has been a longtime pursuit of artificial intelligence (AI) research.
1 code implementation • 28 Sep 2023 • Manuel Milling, Andreas Triantafyllopoulos, Iosif Tsangko, Simon David Noel Rampp, Björn Wolfgang Schuller
The correlation between the sharpness of loss minima and generalisation in the context of deep neural networks has been subject to discussion for a long time.
no code implementations • 15 Sep 2023 • Alexander Gebhard, Andreas Triantafyllopoulos, Teresa Bez, Lukas Christ, Alexander Kathan, Björn W. Schuller
Advances in passive acoustic monitoring and machine learning have led to the procurement of vast datasets for computational bioacoustic research.
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 • 6 Oct 2022 • Andreas Triantafyllopoulos, Björn W. Schuller, Gökçe İymen, Metin Sezgin, Xiangheng He, Zijiang Yang, Panagiotis Tzirakis, Shuo Liu, Silvan Mertes, Elisabeth André, Ruibo Fu, JianHua Tao
Speech is the fundamental mode of human communication, and its synthesis has long been a core priority in human-computer interaction research.
no code implementations • 15 Sep 2022 • Vincent Karas, Andreas Triantafyllopoulos, Meishu Song, Björn W. Schuller
Vocal bursts play an important role in communicating affect, making them valuable for improving speech emotion recognition.
no code implementations • 22 Jun 2022 • Meishu Song, Zijiang Yang, Andreas Triantafyllopoulos, Xin Jing, Vincent Karas, Xie Jiangjian, Zixing Zhang, Yamamoto Yoshiharu, Bjoern W. Schuller
We propose a novel Dynamic Restrained Uncertainty Weighting Loss to experimentally handle the problem of balancing the contributions of multiple tasks on the ICML ExVo 2022 Challenge.
no code implementations • 20 Jun 2022 • Andreas Triantafyllopoulos, Anastasia Semertzidou, Meishu Song, Florian B. Pokorny, Björn W. Schuller
As compared to other existing COVID-19 sound datasets, the unique feature of the COVYT dataset is that it comprises both COVID-19 positive and negative samples from all 65 speakers.
1 code implementation • 14 Jun 2022 • Andreas Triantafyllopoulos, Meishu Song, Zijiang Yang, Xin Jing, Björn W. Schuller
In this work, we explore a novel few-shot personalisation architecture for emotional vocalisation prediction.
no code implementations • 10 May 2022 • Xiangheng He, Andreas Triantafyllopoulos, Alexander Kathan, Manuel Milling, Tianhao Yan, Srividya Tirunellai Rajamani, Ludwig Küster, Mathias Harrer, Elena Heber, Inga Grossmann, David D. Ebert, Björn W. Schuller
Previous studies have shown the correlation between sensor data collected from mobile phones and human depression states.
no code implementations • 9 May 2022 • Andreas Triantafyllopoulos, Sandra Zänkert, Alice Baird, Julian Konzok, Brigitte M. Kudielka, Björn W. Schuller
Stress is a major threat to well-being that manifests in a variety of physiological and mental symptoms.
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 • 6 May 2022 • Alexander Kathan, Andreas Triantafyllopoulos, Xiangheng He, Manuel Milling, Tianhao Yan, Srividya Tirunellai Rajamani, Ludwig Küster, Mathias Harrer, Elena Heber, Inga Grossmann, David D. Ebert, Björn W. Schuller
Digital health applications are becoming increasingly important for assessing and monitoring the wellbeing of people suffering from mental health conditions like depression.
no code implementations • 1 Apr 2022 • Andreas Triantafyllopoulos, Johannes Wagner, Hagen Wierstorf, Maximilian Schmitt, Uwe Reichel, Florian Eyben, Felix Burkhardt, Björn W. Schuller
Large, pre-trained neural networks consisting of self-attention layers (transformers) have recently achieved state-of-the-art results on several speech emotion recognition (SER) datasets.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 31 Mar 2022 • Xin Jing, Shuo Liu, Emilia Parada-Cabaleiro, Andreas Triantafyllopoulos, Meishu Song, Zijiang Yang, Björn W. Schuller
Detecting COVID-19 from audio signals, such as breathing and coughing, can be used as a fast and efficient pre-testing method to reduce the virus transmission.
no code implementations • 29 Mar 2022 • Zijiang Yang, Xin Jing, Andreas Triantafyllopoulos, Meishu Song, Ilhan Aslan, Björn W. Schuller
Emotional voice conversion (EVC) focuses on converting a speech utterance from a source to a target emotion; it can thus be a key enabling technology for human-computer interaction applications and beyond.
1 code implementation • 14 Mar 2022 • Johannes Wagner, Andreas Triantafyllopoulos, Hagen Wierstorf, Maximilian Schmitt, Felix Burkhardt, Florian Eyben, Björn W. Schuller
Recent advances in transformer-based architectures which are pre-trained in self-supervised manner have shown great promise in several machine learning tasks.
no code implementations • 10 Mar 2022 • Björn W. Schuller, Alican Akman, Yi Chang, Harry Coppock, Alexander Gebhard, Alexander Kathan, Esther Rituerto-González, Andreas Triantafyllopoulos, Florian B. Pokorny
We categorise potential computer audition applications according to the five elements of earth, water, air, fire, and aether, proposed by the ancient Greeks in their five element theory; this categorisation serves as a framework to discuss computer audition in relation to different ecological aspects.
no code implementations • 13 Oct 2021 • Andreas Triantafyllopoulos, Uwe Reichel, Shuo Liu, Stephan Huber, Florian Eyben, Björn W. Schuller
In this contribution, we investigate the effectiveness of deep fusion of text and audio features for categorical and dimensional speech emotion recognition (SER).
no code implementations • 4 Oct 2021 • Andreas Triantafyllopoulos, Manuel Milling, Konstantinos Drossos, Björn W. Schuller
Although these factors play a well-understood role in the performance of ASC models, most works report single evaluation metrics taking into account all different strata of a particular dataset.
no code implementations • 3 May 2018 • Andreas Triantafyllopoulos, Hesam Sagha, Florian Eyben, Björn Schuller
This paper describes audEERING's submissions as well as additional evaluations for the One-Minute-Gradual (OMG) emotion recognition challenge.