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pro vyhledávání: '"Choi, Jung-Woo"'
Autor:
Yeon, Inmo, Choi, Jung-Woo
Publikováno v:
Proceedings of the 24th International Congress on Acoustics, ICA 2022
Room geometry inference (RGI) aims at estimating room shapes from measured room impulse responses (RIRs) and has received lots of attention for its importance in environment-aware audio rendering and virtual acoustic representation of a real venue. A
Externí odkaz:
http://arxiv.org/abs/2401.10453
Autor:
Shul, Yusun, Choi, Jung-Woo
Sound event localization and detection (SELD) is a task for the classification of sound events and the localization of direction of arrival (DoA) utilizing multichannel acoustic signals. Prior studies employ spectral and channel information as the em
Externí odkaz:
http://arxiv.org/abs/2312.12821
Accurate estimation of indoor space geometries is vital for constructing precise digital twins, whose broad industrial applications include navigation in unfamiliar environments and efficient evacuation planning, particularly in low-light conditions.
Externí odkaz:
http://arxiv.org/abs/2310.11728
Autor:
Choi, Soonhyeon, Choi, Jung-Woo
Unsupervised anomalous sound detection (ASD) aims to identify anomalous sounds by learning the features of normal operational sounds and sensing their deviations. Recent approaches have focused on the self-supervised task utilizing the classification
Externí odkaz:
http://arxiv.org/abs/2310.06364
Autor:
Yeon, Inmo, Choi, Jung-Woo
Room geometry is important prior information for implementing realistic 3D audio rendering. For this reason, various room geometry inference (RGI) methods have been developed by utilizing the time-of-arrival (TOA) or time-difference-of-arrival (TDOA)
Externí odkaz:
http://arxiv.org/abs/2309.01513
Autor:
Lee, Dongheon, Choi, Jung-Woo
In this work, we present DeFTAN-II, an efficient multichannel speech enhancement model based on transformer architecture and subgroup processing. Despite the success of transformers in speech enhancement, they face challenges in capturing local relat
Externí odkaz:
http://arxiv.org/abs/2308.15777
Localizing sounds and detecting events in different room environments is a difficult task, mainly due to the wide range of reflections and reverberations. When training neural network models with sounds recorded in only a few room environments, there
Externí odkaz:
http://arxiv.org/abs/2306.02591
The drone has been used for various purposes, including military applications, aerial photography, and pesticide spraying. However, the drone is vulnerable to external disturbances, and malfunction in propellers and motors can easily occur. To improv
Externí odkaz:
http://arxiv.org/abs/2304.11708
Autor:
Yi, Wonjun, Choi, Jung-Woo
In-situ classification of faulty sounds is an important issue in machine health monitoring and diagnosis. However, in a noisy environment such as a factory, machine sound is always mixed up with environmental noises, and noise-only periods can exist
Externí odkaz:
http://arxiv.org/abs/2304.03522
Autor:
Lee, Dongheon, Choi, Jung-Woo
Publikováno v:
IEEE Signal Processing Letters, Vol. 30, pp. 155-159, 2023
In this study, we propose a dense frequency-time attentive network (DeFT-AN) for multichannel speech enhancement. DeFT-AN is a mask estimation network that predicts a complex spectral masking pattern for suppressing the noise and reverberation embedd
Externí odkaz:
http://arxiv.org/abs/2212.07570