30 citations · 64 across the 15 of their papers we have counts for
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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.AS2022
CycleGAN-Based Unpaired Speech Dereverberation
Hannah Muckenhirn, Aleksandr Safin, Hakan Erdogan +4
Typically, neural network-based speech dereverberation models are trained on paired data, composed of a dry utterance and its corresponding reverberant utterance. The main limitati…