Sung-Feng Huang

Systematic biases in LALMs can be triggered by subtle cues like gender and accent, revealing a complex landscape of fairness that traditional benchmarks miss.

Speech-to-speech translation can now convey laughter and tears with human-like fidelity, thanks to a surprisingly data-efficient approach leveraging LoRA experts.

High-frequency details, often discarded, are actually crucial for spotting singing voice deepfakes, enabling significantly better detection.