activity
20202022
most citedUsing Deep Learning and Explainable Artificial Intelligence in Patients' Choices of Hospital Levels

4 citations · 5 across the 7 of their papers we have counts for

collaborators

9 papers

cs.SD2022

On the robustness of non-intrusive speech quality model by adversarial examples

Hsin-Yi Lin, Huan-Hsin Tseng, Yu Tsao

It has been shown recently that deep learning based models are effective on speech quality prediction and could outperform traditional metrics in various perspectives. Although net…

eess.AS2022

Inference and Denoise: Causal Inference-based Neural Speech Enhancement

Tsun-An Hsieh, Chao-Han Huck Yang, Pin-Yu Chen +2

This study addresses the speech enhancement (SE) task within the causal inference paradigm by modeling the noise presence as an intervention. Based on the potential outcome framewo…

eess.SP2022

ECG Artifact Removal from Single-Channel Surface EMG Using Fully Convolutional Networks

Kuan-Chen Wang, Kai-Chun Liu, Sheng-Yu Peng +1

Electrocardiogram (ECG) artifact contamination often occurs in surface electromyography (sEMG) applications when the measured muscles are in proximity to the heart. Previous studie…

cs.CL2022

When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing

Chao-Han Huck Yang, Jun Qi, Samuel Yen-Chi Chen +2

The rapid development of quantum computing has demonstrated many unique characteristics of quantum advantages, such as richer feature representation and more secured protection on…

eess.AS2022

Partially Fake Audio Detection by Self-attention-based Fake Span Discovery

Haibin Wu, Heng-Cheng Kuo, Naijun Zheng +5

The past few years have witnessed the significant advances of speech synthesis and voice conversion technologies. However, such technologies can undermine the robustness of broadly…

cs.SD20211 cited

SEOFP-NET: Compression and Acceleration of Deep Neural Networks for Speech Enhancement Using Sign-Exponent-Only Floating-Points

Yu-Chen Lin, Cheng Yu, Yi-Te Hsu +3

Numerous compression and acceleration strategies have achieved outstanding results on classification tasks in various fields, such as computer vision and speech signal processing.…