Erdrin Azemi

According to our database1, Erdrin Azemi authored at least 16 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Leveraging saliency-based pre-trained foundation model representations to uncover breathing patterns in speech.
Comput. Speech Lang., 2026

2025
Learning the relative composition of EEG signals using pairwise relative shift pretraining.
CoRR, November, 2025

CPEP: Contrastive Pose-EMG Pre-training Enhances Gesture Generalization on EMG Signals.
CoRR, September, 2025

Foundation Model Hidden Representations for Heart Rate Estimation from Auscultation.
CoRR, May, 2025

Foundation Model Hidden Representations for Heart Rate Estimation from Auscultation.
Proceedings of the 26th Annual Conference of the International Speech Communication Association, 2025

Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Modeling speech emotion with label variance and analyzing performance across speakers and unseen acoustic conditions.
Proceedings of the Proceedings on "I Can't Believe It's Not Better: Challenges in Applied Deep Learning" at ICLR 2025 Workshops, 2025

2024
Promoting cross-modal representations to improve multimodal foundation models for physiological signals.
CoRR, 2024

Generalizable autoregressive modeling of time series through functional narratives.
CoRR, 2024

Model-driven Heart Rate Estimation and Heart Murmur Detection based on Phonocardiogram.
CoRR, 2024

Pre-Trained Foundation Model representations to uncover Breathing patterns in Speech.
CoRR, 2024

Investigating Salient Representations and Label Variance in Dimensional Speech Emotion Analysis.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Frequency-Aware Masked Autoencoders for Multimodal Pretraining on Biosignals.
CoRR, 2023

Pre-Trained Model Representations and Their Robustness Against Noise for Speech Emotion Analysis.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Speech Emotion: Investigating Model Representations, Multi-Task Learning and Knowledge Distillation.
Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

2020
Subject-Aware Contrastive Learning for Biosignals.
CoRR, 2020


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