Zobrazeno 1 - 10
of 567
pro vyhledávání: '"Choi Jung Woo"'
Autor:
Choi, Dayun, Choi, Jung-Woo
We propose a multichannel-to-multichannel target sound extraction (M2M-TSE) framework for separating multichannel target signals from a multichannel mixture of sound sources. Target sound extraction (TSE) isolates a specific target signal using user-
Externí odkaz:
http://arxiv.org/abs/2409.12415
Autor:
Kwon, Younghoo, Choi, Jung-Woo
We present a transformer-based speech-declipping model that effectively recovers clipped signals across a wide range of input signal-to-distortion ratios (SDRs). While recent time-domain deep neural network (DNN)-based declippers have outperformed tr
Externí odkaz:
http://arxiv.org/abs/2409.12416
Autor:
Lee, Dongheon, Choi, Jung-Woo
This paper presents a framework for universal sound separation and polyphonic audio classification, addressing the challenges of separating and classifying individual sound sources in a multichannel mixture. The proposed framework, DeFT-Mamba, utiliz
Externí odkaz:
http://arxiv.org/abs/2409.12413
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
Publikováno v:
in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 32, pp. 4768-4782, 2024
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
Publikováno v:
2024 18th International Workshop on Acoustic Signal Enhancement (IWAENC), Aalborg, Denmark, 2024, pp. 439-443
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