activity
20242026
collaborators

12 papers

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

Personalized Keyword Spotting for User-Defined Keywords Leveraging Text-Independent Speaker Verification

Ming-Hsiang Hu, Kuan-Tang Huang, Chien-Chun Wang +2

User-defined keyword spotting (UD-KWS) enables zero-shot wake-word detection from text, but existing systems learn speaker-invariant representations that cannot reject impostors ut…

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…

eess.AS2026

TG-ASR: Translation-Guided Learning with Parallel Gated Cross Attention for Low-Resource Automatic Speech Recognition

Cheng-Yeh Yang, Chien-Chun Wang, Li-Wei Chen +3

Low-resource automatic speech recognition (ASR) continues to pose significant challenges, primarily due to the limited availability of transcribed data for numerous languages. Whil…

cs.CL2025

CLiFT-ASR: A Cross-Lingual Fine-Tuning Framework for Low-Resource Taiwanese Hokkien Speech Recognition

Hung-Yang Sung, Chien-Chun Wang, Kuan-Tang Huang +4

Automatic speech recognition (ASR) for low-resource languages such as Taiwanese Hokkien is difficult due to the scarcity of annotated data. However, direct fine-tuning on Han-chara…

cs.SD2025

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…

cs.SD2025

SincQDR-VAD: A Noise-Robust Voice Activity Detection Framework Leveraging Learnable Filters and Ranking-Aware Optimization

Chien-Chun Wang, En-Lun Yu, Jeih-Weih Hung +2

Voice activity detection (VAD) is essential for speech-driven applications, but remains far from perfect in noisy and resource-limited environments. Existing methods often lack rob…

cs.SD2025

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…

cs.SD2024

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…

cs.SD2024

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…