10 papers
MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection
Yanqiu Li, Yang Xiao, Jisheng Bai +3
Recent advances in speech synthesis and audio generation have made high-fidelity acoustic forgery low-cost and difficult to attribute, enabling a realistic attack scenario in which…
RAIL: Rethinking Auditory Intelligence in Large Audio-Language Models with a CHC-Grounded Benchmark
Hongyu Jin, Siyi Wang, Yang Xiao +11
Humans process rich auditory environments through various cognitive capabilities such as audio perception, audio reasoning and memory. Despite recent progress in large audio-langua…
Rethinking Continual Learning for Speech and Audio: A Representation-Centric Taxonomy and Open Problems
Yang Xiao, Siyi Wang, Eun-Jung Holden +1
Speech and audio systems operate in inherently non-stationary environments, yet continual learning (CL) research in this domain, especially in the foundation model era, remains fra…
Learning When to Think While Listening in Large Audio-Language Models
Zhiyuan Song, Weici Zhao, Yang Xiao +3
Recent advances in Large Audio-Language Models (LALMs) have made real-time, streaming spoken interaction increasingly practical. In this setting, reasoning quality and responsivene…
Why Can't They Remember? Uncovering Representation and Retrieval Bottlenecks in Multi-Turn Acoustic Memory
Yang Xiao, Siyi Wang, Han Yin +4
Large audio language models (LALMs) process both speech and environmental acoustic cues, yet struggle to retain non-speech information across multi-turn interactions. The performan…
PolyBench: A Benchmark for Compositional Reasoning in Polyphonic Audio
Yuanjian Chen, Yang Xiao, Han Yin +3
Large Audio Language Models (LALMs) are increasingly capable of reasoning over audio, yet existing benchmarks offer limited coverage of reasoning in polyphonic audio, where multipl…
The First Environmental Sound Deepfake Detection Challenge: Benchmarking Robustness, Evaluation, and Insights
Han Yin, Yang Xiao, Rohan Kumar Das +2
Recent progress in audio generation has made it increasingly easy to create highly realistic environmental soundscapes, which can be misused to produce deceptive content, such as f…
Focus Then Listen: An Empirical Study of Plug-and-Play Audio Enhancer for Noise-Robust Large Audio Language Models
Han Yin, Yang Xiao, Younghoo Kwon +2
Large audio language models (LALMs) are a class of foundation models for audio understanding. Existing LALMs tend to degrade significantly in real-world noisy acoustic conditions w…
Temporally Heterogeneous Graph Contrastive Learning for Multimodal Acoustic event Classification
Yuanjian Chen, Yang Xiao, Jinjie Huang
Multimodal acoustic event classification plays a key role in audio-visual systems. Although combining audio and visual signals improves recognition, it is still difficult to align…
Noise-Robust Sound Event Detection and Counting via Language-Queried Sound Separation
Yuanjian Chen, Yang Xiao, Han Yin +2
Most sound event detection (SED) systems perform well on clean datasets but degrade significantly in noisy environments. Language-queried audio source separation (LASS) models show…