1 citations · 1 across the 11 of their papers we have counts for
11 papers
Anchoring Speech with Semantics: A Multimodal Adapter Mechanism for Automatic Speech Recognition in Low-Resource Languages
Kuan-Tang Huang, Cheng-Yeh Yang, Chien-Chun Wang +3
Low-resource ASR remains difficult because scarce transcripts provide limited supervised evidence for target-side generation. To address this gap, we propose SAMA-ASR, a lightweigh…
DeRA-MOS: Optimizing Text-to-Music Evaluation via Decoupled Listwise Ranking and Modality Alignment
Chien-Chun Wang, Hung-Shin Lee, Hsin-Min Wang +1
Evaluating text-to-music (TTM) systems remains expensive because music impression (MI) and text alignment (TA) scores rely on human mean opinion scores (MOS). Most automatic MOS es…
Robust Generative Audio Quality Assessment: Disentangling Quality from Spurious Correlations
Kuan-Tang Huang, Chien-Chun Wang, Cheng-Yeh Yang +3
The rapid proliferation of AI-Generated Content (AIGC) has necessitated robust metrics for perceptual quality assessment. However, automatic Mean Opinion Score (MOS) prediction mod…
Universal Robust Speech Adaptation for Cross-Domain Speech Recognition and Enhancement
Chien-Chun Wang, Hung-Shin Lee, Hsin-Min Wang +1
Pre-trained models for automatic speech recognition (ASR) and speech enhancement (SE) have exhibited remarkable capabilities under matched noise and channel conditions. However, th…
Efficient Dialect-Aware Modeling and Conditioning for Low-Resource Taiwanese Hakka Speech Processing
An-Ci Peng, Kuan-Tang Huang, Tien-Hong Lo +3
Taiwanese Hakka is a low-resource, endangered language that poses significant challenges for automatic speech recognition (ASR), including high dialectal variability and the presen…
DRASP: A Dual-Resolution Attentive Statistics Pooling Framework for Automatic MOS Prediction
Cheng-Yeh Yang, Kuan-Tang Huang, Chien-Chun Wang +3
A pooling mechanism is essential for mean opinion score (MOS) prediction, facilitating the transformation of variable-length audio features into a concise fixed-size representation…
Revealing the Role of Audio Channels in ASR Performance Degradation
Kuan-Tang Huang, Li-Wei Chen, Hung-Shin Lee +2
Pre-trained automatic speech recognition (ASR) models have demonstrated strong performance on a variety of tasks. However, their performance can degrade substantially when the inpu…
QAMRO: Quality-aware Adaptive Margin Ranking Optimization for Human-aligned Assessment of Audio Generation Systems
Chien-Chun Wang, Kuan-Tang Huang, Cheng-Yeh Yang +3
Evaluating audio generation systems, including text-to-music (TTM), text-to-speech (TTS), and text-to-audio (TTA), remains challenging due to the subjective and multi-dimensional n…
Effective Noise-aware Data Simulation for Domain-adaptive Speech Enhancement Leveraging Dynamic Stochastic Perturbation
Chien-Chun Wang, Li-Wei Chen, Hung-Shin Lee +2
Cross-domain speech enhancement (SE) is often faced with severe challenges due to the scarcity of noise and background information in an unseen target domain, leading to a mismatch…
Channel-Aware Domain-Adaptive Generative Adversarial Network for Robust Speech Recognition
Chien-Chun Wang, Li-Wei Chen, Cheng-Kang Chou +3
While pre-trained automatic speech recognition (ASR) systems demonstrate impressive performance on matched domains, their performance often degrades when confronted with channel mi…
Exploring the Impact of Data Quantity on ASR in Extremely Low-resource Languages
Yao-Fei Cheng, Li-Wei Chen, Hung-Shin Lee +1
This study investigates the efficacy of data augmentation techniques for low-resource automatic speech recognition (ASR), focusing on two endangered Austronesian languages, Amis an…