3 citations · 8 across the 35 of their papers we have counts for
21 papers · 1 filter
CAAD: Contrastive Audio-Aware Distillation for Efficient Speech Language Models
Chun-Wei Chen, Tzu-Quan Lin, Ke-Han Lu +2
Speech Language Models achieve reasoning capabilities, but are often hindered by massive parameter counts and a tendency to prioritize linguistic priors over acoustic features. Whi…
Speaker Identity in Non-Verbal Vocalizations: Conditional Distillation and Mixture of Experts Approach
Tzu-Chieh Wei, Yi-Cheng Lin, Huang-Cheng Chou +4
As expressive text-to-speech (TTS) and voice conversion (VC) systems increasingly generate non-verbal vocalizations (NVVs) to enhance naturalness, reliable speaker verification (SV…
Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI
Yi-Cheng Lin, Yun-Shao Tsai, Kuan-Yu Chen +6
Speech technologies are deployed in high-stakes settings, yet fairness concerns remain fragmented across tasks and disciplines. Existing surveys either adopt a general machine-lear…
VIBE: Voice-Induced open-ended Bias Evaluation for Large Audio-Language Models via Real-World Speech
Yi-Cheng Lin, Yusuke Hirota, Sung-Feng Huang +1
Large Audio-Language Models (LALMs) are increasingly integrated into daily applications, yet their generative biases remain underexplored. Existing speech fairness benchmarks rely…
TAU: A Benchmark for Cultural Sound Understanding Beyond Semantics
Yi-Cheng Lin, Yu-Hua Chen, Jia-Kai Dong +12
Large audio-language models are advancing rapidly, yet most evaluations emphasize speech or globally sourced sounds, overlooking culturally distinctive cues. This gap raises a crit…
Do You Hear What I Mean? Quantifying the Instruction-Perception Gap in Instruction-Guided Expressive Text-To-Speech Systems
Yi-Cheng Lin, Huang-Cheng Chou, Tzu-Chieh Wei +2
Instruction-guided text-to-speech (ITTS) enables users to control speech generation through natural language prompts, offering a more intuitive interface than traditional TTS. Howe…