Marvin Sach

2 accepted papers

2026

ICASSP 2026 URGENT Speech Enhancement Challenge

Chenda Li, Marvin Sach, Wangyou Zhang, Kohei Saijo, Samuele Cornell, Yihui Fu +4

ICASSP 2026poster

The ICASSP 2026 URGENT Challenge advances the series by focusing on universal speech enhancement (SE) systems that handle diverse distortions, domains, and input conditions. This overview paper details the challenge's motivation, task definitions, datasets, baseline systems, evaluation protocols, an…

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2024

Employing Real Training Data for Deep Noise Suppression

Ziyi Xu, Marvin Sach, Jan Pirklbauer, Tim Fingscheidt

ICASSP 2024accepted

Most deep noise suppression (DNS) models are trained with reference-based losses requiring access to clean speech. However, sometimes an additive microphone model is insufficient for real-world applications. Accordingly, ways to use real training data in supervised learning for DNS models promise to…

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