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20242026
most citedExploring the Impact of Data Quantity on ASR in Extremely Low-resource Languages

1 citations · 1 across the 11 of their papers we have counts for

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cs.CL2026

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…

eess.AS2026

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…

eess.AS2026

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…

eess.AS2026

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…

cs.CL2026

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…