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19,880 results on '"Choi, In-Jin"'

101. Few-shot Long-Tailed Bird Audio Recognition

Author

Conde, Marcos V. and Choi, Ui-Jin

Subjects
Computer Science - Sound, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

It is easier to hear birds than see them. However, they still play an essential role in nature and are excellent indicators of deteriorating environmental quality and pollution. Recent advances in Deep Neural Networks allow us to process audio data to detect and classify birds. This technology can assist researchers in monitoring bird populations and biodiversity. We propose a sound detection and classification pipeline to analyze complex soundscape recordings and identify birdcalls in the background. Our method learns from weak labels and few data and acoustically recognizes the bird species. Our solution achieved 18th place of 807 teams at the BirdCLEF 2022 Challenge hosted on Kaggle., Comment: LifeCLEF2022 (best paper award)

Published
2022

102. An isogeometric finite element formulation for frictionless contact of Cosserat rods with unconstrained directors

Author

Choi, Myung-Jin, Klinkel, Sven, and Sauer, Roger A.

Subjects
Mathematics - Numerical Analysis, Physics - Applied Physics
Abstract

This paper presents an isogeometric finite element formulation for nonlinear beams with impenetrability constraints, based on the kinematics of Cosserat rods with unconstrained directors. The beam cross-sectional deformation is represented by director vectors of an arbitrary order. For the frictionless lateral beam-to-beam contact, a surface-to-surface contact algorithm combined with an active set strategy and a penalty method is employed. The lateral boundary surface of the beam is parameterized by its axis and cross-sectional boundary curves with NURBS basis functions having at least $C^2$-continuity, which yields a continuous surface metric and curvature for the closest point projection. Three-dimensional constitutive laws of hyperelastic materials are considered. Several numerical examples verify the accuracy and efficiency of the proposed beam contact formulation in comparison to brick element solutions. The lateral contact pressure distribution of the beam formulation is in excellent agreement with the contact pressure of the brick element formulation while requiring much less degrees-of-freedom., Comment: 44 pages, 36 figures

Published
2022

123. Loss of biochemical response at any time worsens outcomes in UDCA-treated patients with primary biliary cholangitis

Author

Roberts, Surain B., Choi, Woo Jin, Worobetz, Lawrence, Vincent, Catherine, Flemming, Jennifer A., Cheung, Angela, Qumosani, Karim, Swain, Mark, Grbic, Dusanka, Ko, Hin Hin, Peltekian, Kevork M., Abrahamyan, Lusine, Saini, Monika, Tirona, Kattleya, Aziz, Bishoi, Lytvyak, Ellina, Invernizzi, Pietro, Ponsioen, Cyriel Y., Bruns, Tony, Cazzagon, Nora, Lindor, Keith, Dalekos, George N., Gatselis, Nikolaos K., Verhelst, Xavier, Floreani, Annarosa, Corpechot, Christophe, Mayo, Marlyn J., Levy, Cynthia, Londoño, Maria-Carlota, Battezzati, Pier M., Pares, Albert, Nevens, Frederik, van der Meer, Adriaan, Kowdley, Kris V., Trivedi, Palak J., Lleo, Ana, Thorburn, Douglas, Carbone, Marco, Selzner, Nazia, Gulamhusein, Aliya F., Janssen, Harry LA., Montano-Loza, Aldo J., Mason, Andrew L., Hirschfield, Gideon M., and Hansen, Bettina E.

Published
2024
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134. Immunogenicity and protection of a triple repeat domain III mRNA vaccine against Zika virus

Author

Lee, Yu-Sun, Cheong, Mi Sun, Lee, Jisun, Bang, Eun-Kyoung, Park, Sang In, Park, Hyo-Jung, Bae, Seo-Hyeon, Yoon, Subin, Roh, Gahyun, Lee, Seonghyun, Cho, Youngran, Ha, Dahyeon, Oh, Ayoung, Lee, Soo-Yeon, Choi, Eun-Jin, Choi, Huijeong, Jo, Sohee, Lee, Yeeun, Kim, Jungmin, Kwak, Hye Won, Bang, Yoo-Jin, Lee, Dabin, Shim, Heeyoun, Park, Young Kun, Keum, Gyochang, Nam, Jae-Hwan, and Kim, Wonil

Published
2025
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138. Transfer Learning Framework for Low-Resource Text-to-Speech using a Large-Scale Unlabeled Speech Corpus

Author

Kim, Minchan, Jeong, Myeonghun, Choi, Byoung Jin, Ahn, Sunghwan, Lee, Joun Yeop, and Kim, Nam Soo

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Machine Learning
Abstract

Training a text-to-speech (TTS) model requires a large scale text labeled speech corpus, which is troublesome to collect. In this paper, we propose a transfer learning framework for TTS that utilizes a large amount of unlabeled speech dataset for pre-training. By leveraging wav2vec2.0 representation, unlabeled speech can highly improve performance, especially in the lack of labeled speech. We also extend the proposed method to zero-shot multi-speaker TTS (ZS-TTS). The experimental results verify the effectiveness of the proposed method in terms of naturalness, intelligibility, and speaker generalization. We highlight that the single speaker TTS model fine-tuned on the only 10 minutes of labeled dataset outperforms the other baselines, and the ZS-TTS model fine-tuned on the only 30 minutes of single speaker dataset can generate the voice of the arbitrary speaker, by pre-training on unlabeled multi-speaker speech corpus., Comment: Accepted by Interspeech2022

Published
2022
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