Search Results for author: Chiou-Shann Fuh

Found 8 papers, 3 papers with code

MBI-Net: A Non-Intrusive Multi-Branched Speech Intelligibility Prediction Model for Hearing Aids

no code implementations7 Apr 2022 Ryandhimas E. Zezario, Fei Chen, Chiou-Shann Fuh, Hsin-Min Wang, Yu Tsao

In this study, we propose a multi-branched speech intelligibility prediction model (MBI-Net), for predicting the subjective intelligibility scores of HA users.

Deep Learning-based Non-Intrusive Multi-Objective Speech Assessment Model with Cross-Domain Features

1 code implementation3 Nov 2021 Ryandhimas E. Zezario, Szu-Wei Fu, Fei Chen, Chiou-Shann Fuh, Hsin-Min Wang, Yu Tsao

In this study, we propose a cross-domain multi-objective speech assessment model called MOSA-Net, which can estimate multiple speech assessment metrics simultaneously.

Speech Enhancement

Multi-task Federated Learning for Heterogeneous Pancreas Segmentation

no code implementations19 Aug 2021 Chen Shen, Pochuan Wang, Holger R. Roth, Dong Yang, Daguang Xu, Masahiro Oda, Weichung Wang, Chiou-Shann Fuh, Po-Ting Chen, Kao-Lang Liu, Wei-Chih Liao, Kensaku MORI

Federated learning (FL) for medical image segmentation becomes more challenging in multi-task settings where clients might have different categories of labels represented in their data.

Federated Learning Pancreas Segmentation +1

Speech Enhancement with Zero-Shot Model Selection

1 code implementation17 Dec 2020 Ryandhimas E. Zezario, Chiou-Shann Fuh, Hsin-Min Wang, Yu Tsao

Experimental results confirmed that the proposed ZMOS approach can achieve better performance in both seen and unseen noise types compared to the baseline systems and other model selection systems, which indicates the effectiveness of the proposed approach in providing robust SE performance.

Ensemble Learning Model Selection +2

STOI-Net: A Deep Learning based Non-Intrusive Speech Intelligibility Assessment Model

1 code implementation9 Nov 2020 Ryandhimas E. Zezario, Szu-Wei Fu, Chiou-Shann Fuh, Yu Tsao, Hsin-Min Wang

To overcome this limitation, we propose a deep learning-based non-intrusive speech intelligibility assessment model, namely STOI-Net.

Dimensionality Reduction for Data in Multiple Feature Representations

no code implementations NeurIPS 2008 Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh

In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance.

Dimensionality Reduction Graph Embedding +1

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