50 citations · 160 across the 34 of their papers we have counts for
16 papers · 1 filter
EmoSURA: Towards Accurate Evaluation of Detailed and Long-Context Emotional Speech Captions
Xin Jing, Andreas Triantafyllopoulos, Jiadong Wang +3
Recent advancements in speech captioning models have enabled the generation of rich, fine-grained captions for emotional speech. However, the evaluation of such captions remains a…
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…
Non-Verbal Vocalisations and their Challenges: Emotion, Privacy, Sparseness, and Real Life
Anton Batliner, Shahin Amiriparian, Björn W. Schuller
Non-Verbal Vocalisations (NVVs) are short `non-word' utterances without proper linguistic (semantic) meaning but conveying connotations -- be this emotions/affects or other paralin…
This Paper Had the Smartest Reviewers -- Flattery Detection Utilising an Audio-Textual Transformer-Based Approach
Lukas Christ, Shahin Amiriparian, Friederike Hawighorst +5
Flattery is an important aspect of human communication that facilitates social bonding, shapes perceptions, and influences behavior through strategic compliments and praise, levera…
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…
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…
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 voice of COVID-19: Acoustic correlates of infection
Katrin D. Bartl-Pokorny, Florian B. Pokorny, Anton Batliner +8
COVID-19 is a global health crisis that has been affecting many aspects of our daily lives throughout the past year. The symptomatology of COVID-19 is heterogeneous with a severity…
auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks
Michael Freitag, Shahin Amiriparian, Sergey Pugachevskiy +2
auDeep is a Python toolkit for deep unsupervised representation learning from acoustic data. It is based on a recurrent sequence to sequence autoencoder approach which can learn re…