9 citations · 41 across the 18 of their papers we have counts for
19 papers
SmoothCLAP: Soft-Target Enhanced Contrastive Language\--Audio Pretraining for Affective Computing
Xin Jing, Jiadong Wang, Andreas Triantafyllopoulos +4
The ambiguity of human emotions poses several challenges for machine learning models, as they often overlap and lack clear delineating boundaries. Contrastive language-audio pretra…
Exploring Gender-Specific Speech Patterns in Automatic Suicide Risk Assessment
Maurice Gerczuk, Shahin Amiriparian, Justina Lutz +4
In emergency medicine, timely intervention for patients at risk of suicide is often hindered by delayed access to specialised psychiatric care. To bridge this gap, we introduce a s…
ExHuBERT: Enhancing HuBERT Through Block Extension and Fine-Tuning on 37 Emotion Datasets
Shahin Amiriparian, Filip Packań, Maurice Gerczuk +1
Foundation models have shown great promise in speech emotion recognition (SER) by leveraging their pre-trained representations to capture emotion patterns in speech signals. To fur…
The MuSe 2024 Multimodal Sentiment Analysis Challenge: Social Perception and Humor Recognition
Shahin Amiriparian, Lukas Christ, Alexander Kathan +8
The Multimodal Sentiment Analysis Challenge (MuSe) 2024 addresses two contemporary multimodal affect and sentiment analysis problems: In the Social Perception Sub-Challenge (MuSe-P…
Sustained Vowels for Pre- vs Post-Treatment COPD Classification
Andreas Triantafyllopoulos, Anton Batliner, Wolfgang Mayr +6
Chronic obstructive pulmonary disease (COPD) is a serious inflammatory lung disease affecting millions of people around the world. Due to an obstructed airflow from the lungs, it a…
Non-Invasive Suicide Risk Prediction Through Speech Analysis
Shahin Amiriparian, Maurice Gerczuk, Justina Lutz +5
The delayed access to specialized psychiatric assessments and care for patients at risk of suicidal tendencies in emergency departments creates a notable gap in timely intervention…
The ACM Multimedia 2023 Computational Paralinguistics Challenge: Emotion Share & Requests
Björn W. Schuller, Anton Batliner, Shahin Amiriparian +10
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…
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…
Computational Charisma -- A Brick by Brick Blueprint for Building Charismatic Artificial Intelligence
Björn W. Schuller, Shahin Amiriparian, Anton Batliner +6
Charisma is considered as one's ability to attract and potentially also influence others. Clearly, there can be considerable interest from an artificial intelligence's (AI) perspec…
Distinguishing between pre- and post-treatment in the speech of patients with chronic obstructive pulmonary disease
Andreas Triantafyllopoulos, Markus Fendler, Anton Batliner +4
Chronic obstructive pulmonary disease (COPD) causes lung inflammation and airflow blockage leading to a variety of respiratory symptoms; it is also a leading cause of death and aff…
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…
Fatigue Prediction in Outdoor Running Conditions using Audio Data
Andreas Triantafyllopoulos, Sandra Ottl, Alexander Gebhard +9
Although running is a common leisure activity and a core training regiment for several athletes, between and of runners sustain an overuse injury each year. These inj…
A Summary of the ComParE COVID-19 Challenges
Harry Coppock, Alican Akman, Christian Bergler +17
The COVID-19 pandemic has caused massive humanitarian and economic damage. Teams of scientists from a broad range of disciplines have searched for methods to help governments and c…
A Machine Learning Framework for Automatic Prediction of Human Semen Motility
Sandra Ottl, Shahin Amiriparian, Maurice Gerczuk +1
In this paper, human semen samples from the visem dataset collected by the Simula Research Laboratory are automatically assessed with machine learning methods for their quality in…
DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing from Decentralised Data
Shahin Amiriparian, Tobias Hübner, Maurice Gerczuk +2
Deep neural speech and audio processing systems have a large number of trainable parameters, a relatively complex architecture, and require a vast amount of training data and compu…
On the Impact of Word Error Rate on Acoustic-Linguistic Speech Emotion Recognition: An Update for the Deep Learning Era
Shahin Amiriparian, Artem Sokolov, Ilhan Aslan +9
Text encodings from automatic speech recognition (ASR) transcripts and audio representations have shown promise in speech emotion recognition (SER) ever since. Yet, it is challengi…
EmoNet: A Transfer Learning Framework for Multi-Corpus Speech Emotion Recognition
Maurice Gerczuk, Shahin Amiriparian, Sandra Ottl +1
In this manuscript, the topic of multi-corpus Speech Emotion Recognition (SER) is approached from a deep transfer learning perspective. A large corpus of emotional speech data, Emo…
The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates
Björn W. Schuller, Anton Batliner, Christian Bergler +21
The INTERSPEECH 2021 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the CO…
A Novel Fusion of Attention and Sequence to Sequence Autoencoders to Predict Sleepiness From Speech
Shahin Amiriparian, Pawel Winokurow, Vincent Karas +3
Motivated by the attention mechanism of the human visual system and recent developments in the field of machine translation, we introduce our attention-based and recurrent sequence…