7 citations · 18 across the 9 of their papers we have counts for
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cs.SD2026
MixProLAP: Mixture-Induced Uncertainty Modeling for Probabilistic Language-Audio Pretraining
Yu Nakagome, Jaesong Lee, Soo-Whan Chung
Acoustic environments often contain multiple overlapping sound events, and the same acoustic scene can be described using diverse textual expressions, making audio-text alignment i…
cs.SD2022★ 4 cited
Large-scale learning of generalised representations for speaker recognition
Jee-weon Jung, Hee-Soo Heo, Bong-Jin Lee +5
The objective of this work is to develop a speaker recognition model to be used in diverse scenarios. We hypothesise that two components should be adequately configured to build su…