3 citations · 6 across the 6 of their papers we have counts for
6 papers
MTI-Net: A Multi-Target Speech Intelligibility Prediction Model
Ryandhimas E. Zezario, Szu-wei Fu, Fei Chen +3
Recently, deep learning (DL)-based non-intrusive speech assessment models have attracted great attention. Many studies report that these DL-based models yield satisfactory assessme…
MBI-Net: A Non-Intrusive Multi-Branched Speech Intelligibility Prediction Model for Hearing Aids
Ryandhimas E. Zezario, Fei Chen, Chiou-Shann Fuh +2
Improving the user's hearing ability to understand speech in noisy environments is critical to the development of hearing aid (HA) devices. For this, it is important to derive a me…
Deep Learning-based Non-Intrusive Multi-Objective Speech Assessment Model with Cross-Domain Features
Ryandhimas E. Zezario, Szu-Wei Fu, Fei Chen +3
In this study, we propose a cross-domain multi-objective speech assessment model called MOSA-Net, which can estimate multiple speech assessment metrics simultaneously. Experimental…
The effect of speech and noise levels on the quality perceived by cochlear implant and normal hearing listeners
Sara Akbarzadeh, Sungmin Lee, Fei Chen +1
Electrical hearing by cochlear implants (CIs) may be fundamentally different from acoustic hearing by normal-hearing (NH) listeners, presumably showing unequal speech quality perce…
Eye-gaze Estimation with HEOG and Neck EMG using Deep Neural Networks
Zhen Fu, Bo Wang, Fei Chen +2
Hearing-impaired listeners usually have troubles attending target talker in multi-talker scenes, even with hearing aids (HAs). The problem can be solved with eye-gaze steering HAs,…
Speech Dereverberation Based on Integrated Deep and Ensemble Learning Algorithm
Wei-Jen Lee, Syu-Siang Wang, Fei Chen +3
Reverberation, which is generally caused by sound reflections from walls, ceilings, and floors, can result in severe performance degradation of acoustic applications. Due to a comp…