3 papers
cs.SD2026
GRAM: Spatial general-purpose audio representations for real-world environments
Goksenin Yuksel, Marcel van Gerven, Kiki van der Heijden
Audio foundation models learn general-purpose audio representations that facilitate a wide range of downstream tasks. While the performance of these models has greatly increased fo…
cs.SD2026
GRAM: Spatial general-purpose audio representation models for real-world applications
Goksenin Yuksel, Marcel van Gerven, Kiki van der Heijden
Audio foundation models learn general-purpose audio representations that facilitate a wide range of downstream tasks. While the performance of these models has greatly increased fo…
cs.SD2025
WavJEPA: Semantic learning unlocks robust audio foundation models for raw waveforms
Goksenin Yuksel, Pierre Guetschel, Michael Tangermann +2
Learning audio representations from raw waveforms overcomes key limitations of spectrogram-based audio representation learning, such as the long latency of spectrogram computation…