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20162024
most citedAddressing Missing Labels in Large-Scale Sound Event Recognition Using a Teacher-Student Framework With Loss Masking

23 citations · 29 across the 6 of their papers we have counts for

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2 papers · 1 filter

eess.AS2022

Text-Driven Separation of Arbitrary Sounds

Kevin Kilgour, Beat Gfeller, Qingqing Huang +3

We propose a method of separating a desired sound source from a single-channel mixture, based on either a textual description or a short audio sample of the target source. This is…

eess.AS2021

Sparse, Efficient, and Semantic Mixture Invariant Training: Taming In-the-Wild Unsupervised Sound Separation

Scott Wisdom, Aren Jansen, Ron J. Weiss +2

Supervised neural network training has led to significant progress on single-channel sound separation. This approach relies on ground truth isolated sources, which precludes scalin…