6 papers
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…
A Multi-Stage Separation-and-Classification Framework Guided by Complementary Acoustic-to-Semantic Clues
Younghoo Kwon, Junwoo Park, Han Yin +1
This report describes the system proposed for the DCASE 2026 Challenge Task 4: Spatial Semantic Segmentation of Sound Scenes (S5). Specifically, we develop a multi-stage framework…
Peak-Detector: Explainable Peak Detection via Instruction-Tuned Large Language Models in Physiological Sign
Jiahui Li, Yida Zhang, Zixuan Zeng +10
Accurate peak detection across diverse cardiac physiological signals, including the Electrocardiogram (ECG), Photoplethysmogram (PPG), Ballistocardiogram (BCG), and Bodyseismograph…
DeepASA: An Object-Oriented Multi-Purpose Network for Auditory Scene Analysis
Dongheon Lee, Younghoo Kwon, Jung-Woo Choi
We propose DeepASA, a multi-purpose model for auditory scene analysis that performs multi-input multi-output (MIMO) source separation, dereverberation, sound event detection (SED),…
Sound Separation and Classification with Object and Semantic Guidance
Younghoo Kwon, Jung-Woo Choi
The spatial semantic segmentation task focuses on separating and classifying sound objects from multichannel signals. To achieve two different goals, conventional methods fine-tune…
Self-Guided Target Sound Extraction and Classification Through Universal Sound Separation Model and Multiple Clues
Younghoo Kwon, Dongheon Lee, Dohwan Kim +1
This paper introduces a multi-stage self-directed framework designed to address the spatial semantic segmentation of sound scene (S5) task in the DCASE 2025 Task 4 challenge. This…