activity
20142025
most citedDeep Unfolding: Model-Based Inspiration of Novel Deep Architectures

255 citations · 1.2k across the 38 of their papers we have counts for

collaborators

43 papers

cs.SD2025

Recomposer: Event-roll-guided generative audio editing

Daniel P. W. Ellis, Eduardo Fonseca, Ron J. Weiss +7

Editing complex real-world sound scenes is difficult because individual sound sources overlap in time. Generative models can fill-in missing or corrupted details based on their str…

cs.SD2024★ 1 cited

Towards Sub-millisecond Latency Real-Time Speech Enhancement Models on Hearables

Artem Dementyev, Chandan K. A. Reddy, Scott Wisdom +3

Low latency models are critical for real-time speech enhancement applications, such as hearing aids and hearables. However, the sub-millisecond latency space for resource-constrain…

cs.SD2024★ 17 cited

Objective and subjective evaluation of speech enhancement methods in the UDASE task of the 7th CHiME challenge

Simon Leglaive, Matthieu Fraticelli, Hend ElGhazaly +7

Supervised models for speech enhancement are trained using artificially generated mixtures of clean speech and noise signals. However, the synthetic training conditions may not acc…

cs.SD2023

TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognition

Hakan Erdogan, Scott Wisdom, Xuankai Chang +4

We present TokenSplit, a speech separation model that acts on discrete token sequences. The model is trained on multiple tasks simultaneously: separate and transcribe each speech s…

cs.SD2023★ 16 cited

The CHiME-7 UDASE task: Unsupervised domain adaptation for conversational speech enhancement

Simon Leglaive, Léonie Borne, Efthymios Tzinis +6

Supervised speech enhancement models are trained using artificially generated mixtures of clean speech and noise signals, which may not match real-world recording conditions at tes…

cs.SD2023

AudioSlots: A slot-centric generative model for audio separation

Pradyumna Reddy, Scott Wisdom, Klaus Greff +2

In a range of recent works, object-centric architectures have been shown to be suitable for unsupervised scene decomposition in the vision domain. Inspired by these methods we pres…