514 citations · 1.2k across the 41 of their papers we have counts for
6 papers · 1 filter
RankUp: Boosting Semi-Supervised Regression with an Auxiliary Ranking Classifier
Pin-Yen Huang, Szu-Wei Fu, Yu Tsao
State-of-the-art (SOTA) semi-supervised learning techniques, such as FixMatch and it's variants, have demonstrated impressive performance in classification tasks. However, these me…
The VoiceMOS Challenge 2024: Beyond Speech Quality Prediction
Wen-Chin Huang, Szu-Wei Fu, Erica Cooper +5
We present the third edition of the VoiceMOS Challenge, a scientific initiative designed to advance research into automatic prediction of human speech ratings. There were three tra…
Exploiting Consistency-Preserving Loss and Perceptual Contrast Stretching to Boost SSL-based Speech Enhancement
Muhammad Salman Khan, Moreno La Quatra, Kuo-Hsuan Hung +3
Self-supervised representation learning (SSL) has attained SOTA results on several downstream speech tasks, but SSL-based speech enhancement (SE) solutions still lag behind. To add…
DeSTA: Enhancing Speech Language Models through Descriptive Speech-Text Alignment
Ke-Han Lu, Zhehuai Chen, Szu-Wei Fu +4
Recent speech language models (SLMs) typically incorporate pre-trained speech models to extend the capabilities from large language models (LLMs). In this paper, we propose a Descr…
An Investigation of Incorporating Mamba for Speech Enhancement
Rong Chao, Wen-Huang Cheng, Moreno La Quatra +4
This work aims to investigate the use of a recently proposed, attention-free, scalable state-space model (SSM), Mamba, for the speech enhancement (SE) task. In particular, we emplo…
Self-Supervised Speech Quality Estimation and Enhancement Using Only Clean Speech
Szu-Wei Fu, Kuo-Hsuan Hung, Yu Tsao +1
Speech quality estimation has recently undergone a paradigm shift from human-hearing expert designs to machine-learning models. However, current models rely mainly on supervised le…