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20232025
most citedURGENT Challenge: Universality, Robustness, and Generalizability For Speech Enhancement

30 citations · 31 across the 7 of their papers we have counts for

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7 papers · 1 filter

eess.AS2025

P.808 Multilingual Speech Enhancement Testing: Approach and Results of URGENT 2025 Challenge

Marvin Sach, Yihui Fu, Kohei Saijo +9

In speech quality estimation for speech enhancement (SE) systems, subjective listening tests so far are considered as the gold standard. This should be even more true considering t…

eess.AS2025

URGENT-PK: Perceptually-Aligned Ranking Model Designed for Speech Enhancement Competition

Jiahe Wang, Chenda Li, Wei Wang +11

The Mean Opinion Score (MOS) is fundamental to speech quality assessment. However, its acquisition requires significant human annotation. Although deep neural network approaches, s…

eess.AS2025

Lessons Learned from the URGENT 2024 Speech Enhancement Challenge

Wangyou Zhang, Kohei Saijo, Samuele Cornell +10

The URGENT 2024 Challenge aims to foster speech enhancement (SE) techniques with great universality, robustness, and generalizability, featuring a broader task definition, large-sc…

eess.AS2025

Interspeech 2025 URGENT Speech Enhancement Challenge

Kohei Saijo, Wangyou Zhang, Samuele Cornell +9

There has been a growing effort to develop universal speech enhancement (SE) to handle inputs with various speech distortions and recording conditions. The URGENT Challenge series…

eess.AS2024★ 30 cited

URGENT Challenge: Universality, Robustness, and Generalizability For Speech Enhancement

Wangyou Zhang, Robin Scheibler, Kohei Saijo +9

The last decade has witnessed significant advancements in deep learning-based speech enhancement (SE). However, most existing SE research has limitations on the coverage of SE sub-…

eess.AS2024

Cross-Talk Reduction

Zhong-Qiu Wang, Anurag Kumar, Shinji Watanabe

While far-field multi-talker mixtures are recorded, each speaker can wear a close-talk microphone so that close-talk mixtures can be recorded at the same time. Although each close-…

eess.AS2023★ 1 cited

TorchAudio 2.1: Advancing speech recognition, self-supervised learning, and audio processing components for PyTorch

Jeff Hwang, Moto Hira, Caroline Chen +21

TorchAudio is an open-source audio and speech processing library built for PyTorch. It aims to accelerate the research and development of audio and speech technologies by providing…