Andrew Bydlon — accepted AI-conference papers

2025

Effective Techniques for Scaling Audio Encoder Pretraining

Byeonggeun Kim, Andrew Bydlon, Qingming Tang, Huy Phan, Chieh-Chi Kao, Tao Zhang +1

ICASSP 2025accepted

This work presents advancements in audio pretraining objectives designed to generate semantically rich embeddings, capable of addressing a wide range of audio-related tasks. Despite significant progress in the field, current methods often emphasize full fine-tuning in downstream applications, which…

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2024

Cross-Triggering Issue in Audio Event Detection and Mitigation

Huy Phan, Byeonggeun Kim, Vu Nguyen, Andrew Bydlon, Qingming Tang, Chieh-Chi Kao +1

ICASSP 2024accepted

Cross-triggering is a critical problem for applications of audio event detection (AED), particularly in low-resource settings. However, not much attention (if not none) has been paid to this problem in the AED research community. In this work, we tackle this problem via a regularization approach. We…

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