collaborators

5 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.SD2025

Speech Separation for Hearing-Impaired Children in the Classroom

Feyisayo Olalere, Kiki van der Heijden, H. Christiaan Stronks +3

Classroom environments are particularly challenging for children with hearing impairments, where background noise, multiple talkers, and reverberation degrade speech perception. Th…

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…

cs.SD2025

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

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…