1 citations · 2 across the 5 of their papers we have counts for
5 papers
Restorative Speech Enhancement: A Progressive Approach Using SE and Codec Modules
Hsin-Tien Chiang, Hao Zhang, Yong Xu +2
In challenging environments with significant noise and reverberation, traditional speech enhancement (SE) methods often lead to over-suppressed speech, creating artifacts during li…
Multi-objective Non-intrusive Hearing-aid Speech Assessment Model
Hsin-Tien Chiang, Szu-Wei Fu, Hsin-Min Wang +2
Without the need for a clean reference, non-intrusive speech assessment methods have caught great attention for objective evaluations. While deep learning models have been used to…
Study on the Correlation between Objective Evaluations and Subjective Speech Quality and Intelligibility
Hsin-Tien Chiang, Kuo-Hsuan Hung, Szu-Wei Fu +3
Subjective tests are the gold standard for evaluating speech quality and intelligibility; however, they are time-consuming and expensive. Thus, objective measures that align with h…
Boosting Self-Supervised Embeddings for Speech Enhancement
Kuo-Hsuan Hung, Szu-wei Fu, Huan-Hsin Tseng +3
Self-supervised learning (SSL) representation for speech has achieved state-of-the-art (SOTA) performance on several downstream tasks. However, there remains room for improvement i…
HASA-net: A non-intrusive hearing-aid speech assessment network
Hsin-Tien Chiang, Yi-Chiao Wu, Cheng Yu +4
Without the need of a clean reference, non-intrusive speech assessment methods have caught great attention for objective evaluations. Recently, deep neural network (DNN) models hav…