Min-Sang Baek — accepted AI-conference papers

2026

Physics-Informed Audio-Geometry-Grid Representation Learning for Universal Sound Source Localization

Min-Sang Baek, Gyeong-Su Kim, Donghyun Kim, Joon-Hyuk Chang

ICLR 2026poster

Sound source localization (SSL) is a fundamental task in spatial audio understanding, yet most deep neural network-based methods are constrained by fixed array geometries and predefined directional grids, limiting generalizability and scalability. To address these issues, we propose _audio-geometry-…

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2024

Improving Target Sound Extraction with Timestamp Knowledge Distillation

Dail Kim, Min-Sang Baek, Yungyeo Kim, Joon-Hyuk Chang

ICASSP 2024accepted

In this paper, we propose a timestamp knowledge distillation (TKD) method that adopts privileged knowledge distillation to enhance the performance of deep neural network (DNN)-based target sound extraction (TSE). While previous studies have mainly used n-hot vectors to indicate the type of target so…

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