40 citations · 110 across the 33 of their papers we have counts for
9 papers · 1 filter
USE: A Unified Model for Universal Sound Separation and Extraction
Hongyu Wang, Chenda Li, Xin Zhou +2
Sound separation (SS) and target sound extraction (TSE) are fundamental techniques for addressing complex acoustic scenarios. While existing SS methods struggle with determining th…
PURE Codec: Progressive Unfolding of Residual Entropy for Speech Codec Learning
Jiatong Shi, Haoran Wang, William Chen +4
Neural speech codecs have achieved strong performance in low-bitrate compression, but residual vector quantization (RVQ) often suffers from unstable training and ineffective decomp…
MeanSE: Efficient Generative Speech Enhancement with Mean Flows
Jiahe Wang, Hongyu Wang, Wei Wang +5
Speech enhancement (SE) improves degraded speech's quality, with generative models like flow matching gaining attention for their outstanding perceptual quality. However, the flow-…
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…
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…
Efficient Multilingual ASR Finetuning via LoRA Language Experts
Jiahong Li, Yiwen Shao, Jianheng Zhuo +4
Recent advancements in deep learning have significantly enhanced multilingual automatic speech recognition (ASR) due to the development of advanced model architectures and availabl…
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…
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…
Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment
Wei Wang, Wangyou Zhang, Chenda Li +3
Speech quality assessment (SQA) aims to predict the perceived quality of speech signals under a wide range of distortions. It is inherently connected to speech enhancement (SE), wh…