53 citations · 171 across the 11 of their papers we have counts for
11 papers
Generative Speech Recognition Error Correction with Large Language Models and Task-Activating Prompting
Chao-Han Huck Yang, Yile Gu, Yi-Chieh Liu +3
We explore the ability of large language models (LLMs) to act as speech recognition post-processors that perform rescoring and error correction. Our first focus is on instruction p…
Low-rank Adaptation of Large Language Model Rescoring for Parameter-Efficient Speech Recognition
Yu Yu, Chao-Han Huck Yang, Jari Kolehmainen +15
We propose a neural language modeling system based on low-rank adaptation (LoRA) for speech recognition output rescoring. Although pretrained language models (LMs) like BERT have s…
Adversarial Reweighting for Speaker Verification Fairness
Minho Jin, Chelsea J. -T. Ju, Zeya Chen +3
We address performance fairness for speaker verification using the adversarial reweighting (ARW) method. ARW is reformulated for speaker verification with metric learning, and show…
Treatment Learning Causal Transformer for Noisy Image Classification
Chao-Han Huck Yang, I-Te Danny Hung, Yi-Chieh Liu +1
Current top-notch deep learning (DL) based vision models are primarily based on exploring and exploiting the inherent correlations between training data samples and their associate…
End-to-end Neural Diarization: From Transformer to Conformer
Yi Chieh Liu, Eunjung Han, Chul Lee +1
We propose a new end-to-end neural diarization (EEND) system that is based on Conformer, a recently proposed neural architecture that combines convolutional mappings and Transforme…
Ensemble-based Transfer Learning for Low-resource Machine Translation Quality Estimation
Ting-Wei Wu, Yung-An Hsieh, Yi-Chieh Liu
Quality Estimation (QE) of Machine Translation (MT) is a task to estimate the quality scores for given translation outputs from an unknown MT system. However, QE scores for low-res…
DeepOpht: Medical Report Generation for Retinal Images via Deep Models and Visual Explanation
Jia-Hong Huang, Chao-Han Huck Yang, Fangyu Liu +9
In this work, we propose an AI-based method that intends to improve the conventional retinal disease treatment procedure and help ophthalmologists increase diagnosis efficiency and…
Interpretable Self-Attention Temporal Reasoning for Driving Behavior Understanding
Yi-Chieh Liu, Yung-An Hsieh, Min-Hung Chen +3
Performing driving behaviors based on causal reasoning is essential to ensure driving safety. In this work, we investigated how state-of-the-art 3D Convolutional Neural Networks (C…
Synthesizing New Retinal Symptom Images by Multiple Generative Models
Yi-Chieh Liu, Hao-Hsiang Yang, Chao-Han Huck Yang +5
Age-Related Macular Degeneration (AMD) is an asymptomatic retinal disease which may result in loss of vision. There is limited access to high-quality relevant retinal images and po…
When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks
Chao-Han Huck Yang, Yi-Chieh Liu, Pin-Yu Chen +2
Discovering and exploiting the causality in deep neural networks (DNNs) are crucial challenges for understanding and reasoning causal effects (CE) on an explainable visual model. "…
Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model
C. -H. Huck Yang, Fangyu Liu, Jia-Hong Huang +6
Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists. Based on the fact that fun…