37 citations · 45 across the 5 of their papers we have counts for
7 papers
Federated learning for violence incident prediction in a simulated cross-institutional psychiatric setting
Thomas Borger, Pablo Mosteiro, Heysem Kaya +4
Inpatient violence is a common and severe problem within psychiatry. Knowing who might become violent can influence staffing levels and mitigate severity. Predictive machine learni…
Speech Analysis for Automatic Mania Assessment in Bipolar Disorder
Pınar Baki, Heysem Kaya, Elvan Çiftçi +2
Bipolar disorder is a mental disorder that causes periods of manic and depressive episodes. In this work, we classify recordings from Bipolar Disorder corpus that contain 7 differe…
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…
Introducing a Central African Primate Vocalisation Dataset for Automated Species Classification
Joeri A. Zwerts, Jelle Treep, Casper S. Kaandorp +3
Automated classification of animal vocalisations is a potentially powerful wildlife monitoring tool. Training robust classifiers requires sizable annotated datasets, which are not…
An Audio-Video Deep and Transfer Learning Framework for Multimodal Emotion Recognition in the wild
Denis Dresvyanskiy, Elena Ryumina, Heysem Kaya +3
In this paper, we present our contribution to ABAW facial expression challenge. We report the proposed system and the official challenge results adhering to the challenge protocol.…
Is Everything Fine, Grandma? Acoustic and Linguistic Modeling for Robust Elderly Speech Emotion Recognition
Gizem Soğancıoğlu, Oxana Verkholyak, Heysem Kaya +4
Acoustic and linguistic analysis for elderly emotion recognition is an under-studied and challenging research direction, but essential for the creation of digital assistants for th…