activity
20242026
collaborators

7 papers

eess.AS2026

Hearing Like Humans? Sound Symbolism and Perceptual Alignment in Speech Language Models

Yun-Shao Tsai, Chun-Wei Chen, Chee-En Yu +2

Sound symbolism, the human tendency to map speech sounds to perceptual qualities such as roundness or sharpness, arises primarily from the acoustics of speech rather than spelling.…

eess.AS2026

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…

eess.AS2026

The False Resonance: A Critical Examination of Emotion Embedding Similarity for Speech Generation Evaluation

Yun-Shao Tsai, Yi-Cheng Lin, Huang-Cheng Chou +5

Objective metrics for emotional expressiveness are vital for speech generation, particularly in expressive synthesis and voice conversion requiring emotional prosody transfer. To q…

cs.CL2026

TaigiSpeech: A Low-Resource Real-World Speech Intent Dataset and Preliminary Results with Scalable Data Mining In-the-Wild

Kai-Wei Chang, Yi-Cheng Lin, Huang-Cheng Chou +9

Speech technologies have advanced rapidly and serve diverse populations worldwide. However, many languages remain underrepresented due to limited resources. In this paper, we intro…

cs.SD2026

MUGEN: Evaluating and Improving Multi-audio Understanding of Large Audio-Language Models

Chih-Kai Yang, Yun-Shao Tsai, Yu-Kai Guo +7

While multi-audio understanding is critical for large audio-language models (LALMs), it remains underexplored. We introduce MUGEN, a comprehensive benchmark evaluating this capabil…

eess.AS2025

CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognition

Yun-Shao Tsai, Yi-Cheng Lin, Huang-Cheng Chou +1

Bias in speech emotion recognition (SER) systems often stems from spurious correlations between speaker characteristics and emotional labels, leading to unfair predictions across d…