36 citations · 161 across the 62 of their papers we have counts for
8 papers · 1 filter
A Multi-dimensional Framework for Evaluating Generalization in EEG Foundation Models
Aditya Kommineni, Emily Zhou, Kleanthis Avramidis +2
Evaluating foundation models under appropriate adaptation settings is essential for understanding the quality and transferability of the learned representations. Recent EEG foundat…
Aperiodic and Low-Frequency Spectral Bias in Reconstruction based EEG Foundation Models
Aditya Kommineni, Emily Zhou, Kleanthis Avramidis +7
EEG foundation models, pre-trained on large-scale unlabelled EEG data, have emerged as a promising direction towards learning generalizable EEG representations. Despite showing pos…
Neural Codecs as Biosignal Tokenizers
Kleanthis Avramidis, Tiantian Feng, Woojae Jeong +4
Neurophysiological recordings such as electroencephalography (EEG) offer accessible and minimally invasive means of estimating physiological activity for applications in healthcare…
Developing a High-performance Framework for Speech Emotion Recognition in Naturalistic Conditions Challenge for Emotional Attribute Prediction
Thanathai Lertpetchpun, Tiantian Feng, Dani Byrd +1
Speech emotion recognition (SER) in naturalistic conditions presents a significant challenge for the speech processing community. Challenges include disagreement in labeling among…
Examining Test-Time Adaptation for Personalized Child Speech Recognition
Zhonghao Shi, Xuan Shi, Anfeng Xu +4
Automatic speech recognition (ASR) models often experience performance degradation due to data domain shifts introduced at test time, a challenge that is further amplified for chil…
Scaling Representation Learning from Ubiquitous ECG with State-Space Models
Kleanthis Avramidis, Dominika Kunc, Bartosz Perz +5
Ubiquitous sensing from wearable devices in the wild holds promise for enhancing human well-being, from diagnosing clinical conditions and measuring stress to building adaptive hea…