Zobrazeno 1 - 10 of 108 pro vyhledávání: '"Sung-joo LEE"'
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Akademický článek
Semi-Supervised Speech Recognition Acoustic Model Training Using Policy Gradient
Autor: Hoon Chung, Sung Joo Lee, Hyeong Bae Jeon, Jeon Gue Park
Publikováno v: Applied Sciences, Vol 10, Iss 10, p 3542 (2020)
In this paper, we propose a policy gradient-based semi-supervised speech recognition acoustic model training. In practice, self-training and teacher/student learning are one of the widely used semi-supervised training methods due to their scalability
Externí odkaz: https://doaj.org/article/9584ab1b2bc3473884405a4bf480e4a5
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6
Cross-Corpus Speech Emotion Recognition Based on Few-Shot Learning and Domain Adaptation
Autor: Sung Joo Lee, Jong Won Shin, Youngdo Ahn
Publikováno v: IEEE Signal Processing Letters. 28:1190-1194
Within a single speech emotion corpus, deep neural networks have shown decent performance in speech emotion recognition. However, the performance of the emotion recognition based on data-driven learning methods degrades significantly for the cross-co
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a3ecffe29bc4c6ab87ca3ce28d8b0bbc
https://doi.org/10.1109/lsp.2021.3086395
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9
Spatialization and Prediction of Seasonal NO2 Pollution Due to Climate Change in the Korean Capital Area through Land Use Regression Modeling
Autor: No Ol Lim, Jinhoo Hwang, Sung-Joo Lee, Youngjae Yoo, Yuyoung Choi, Seongwoo Jeon
Publikováno v: International Journal of Environmental Research and Public Health; Volume 19; Issue 9; Pages: 5111
Urbanization is causing an increase in air pollution leading to serious health issues. However, even though the necessity of its regulation is acknowledged, there are relatively few monitoring sites in the capital metropolitan city of the Republic of
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18a67a0a587bc372d8c06b00d46b8d87
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10
Akademický článek
Nonnegative Matrix Factorization Based Adaptive Noise Sensing over Wireless Sensor Networks
Autor: Kwang Myung Jeon, Hong Kook Kim, Sung Joo Lee, Yun Keun Lee
Publikováno v: International Journal of Distributed Sensor Networks, Vol 10 (2014)
An adaptive noise sensing method is proposed to improve the speech sensing performance of speech-based applications operated over wireless sensor networks. The proposed method is based on nonnegative matrix factorization (NMF), which consists of adap
Externí odkaz: https://doaj.org/article/8d144cb2ab8f4e4182e3036c48b45dd4
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