1.1k citations · 1.7k across the 56 of their papers we have counts for
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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…
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…
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…
Leveraging Spatial Cues from Cochlear Implant Microphones to Efficiently Enhance Speech Separation in Real-World Listening Scenes
Feyisayo Olalere, Kiki van der Heijden, Christiaan H. Stronks +3
Speech separation approaches for single-channel, dry speech mixtures have significantly improved. However, real-world spatial and reverberant acoustic environments remain challengi…