Jongmo Sung

18 papers A 4Misc 5Journal 9
YearRankTypeTitle / Venue / Authors
2024 J jnl
Optimizations of Neural Audio Coder Toward Perceptual Transparency.
IEEE J. Sel. Top. Signal Process.
Joon Byun, Seungmin Shin, Seorim Hwang, Jongmo Sung, Seungkwon Beack, Youngcheol Park
2024 Misc conf
Quantization Noise Masking in Perceptual Neural Audio Coder.
ICASSP
Seungmin Shin, Joon Byun, Jongmo Sung, Seungkwon Beack, Youngcheol Park
2023 Misc conf
A Perceptual Neural Audio Coder with a Mean-Scale Hyperprior.
ICASSP
Joon Byun, Seungmin Shin, Youngcheol Park, Jongmo Sung, Seungkwon Beack
2023 A conf
Perceptual Improvement of Deep Neural Network (DNN) Speech Coder Using Parametric and Non-parametric Density Models.
INTERSPEECH
Joon Byun, Seungmin Shin, Jongmo Sung, Seungkwon Beack, Youngcheol Park
2022 Misc conf
Deep Neural Network (DNN) Audio Coder Using A Perceptually Improved Training Method.
ICASSP
Seungmin Shin, Joon Byun, Youngcheol Park, Jongmo Sung, Seungkwon Beack
2022 A conf
Optimization of Deep Neural Network (DNN) Speech Coder Using a Multi Time Scale Perceptual Loss Function.
INTERSPEECH
Joon Byun, Seungmin Shin, Jongmo Sung, Seungkwon Beack, Youngcheol Park
2022 J jnl
Scalable and Efficient Neural Speech Coding: A Hybrid Design.
IEEE ACM Trans. Audio Speech Lang. Process.
Kai Zhen, Jongmo Sung, Mi Suk Lee, Seungkwon Beack, Minje Kim
2021 A conf
Development of a Psychoacoustic Loss Function for the Deep Neural Network (DNN)-Based Speech Coder.
Interspeech
Joon Byun, Seungmin Shin, Youngcheol Park, Jongmo Sung, Seungkwon Beack
2021 J jnl
Psychoacoustic Calibration of Loss Functions for Efficient End-to-End Neural Audio Coding.
CoRR
Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, Minje Kim
2021 J jnl
Scalable and Efficient Neural Speech Coding.
CoRR
Kai Zhen, Jongmo Sung, Mi Suk Lee, Seungkwon Beack, Minje Kim
2020 J jnl
Efficient And Scalable Neural Residual Waveform Coding With Collaborative Quantization.
CoRR
Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, Minje Kim
2020 Misc conf
Efficient and Scalable Neural Residual Waveform Coding with Collaborative Quantization.
ICASSP
Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, Minje Kim
2020 J jnl
Psychoacoustic Calibration of Loss Functions for Efficient End-to-End Neural Audio Coding.
IEEE Signal Process. Lett.
Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, Minje Kim
2019 A conf
Cascaded Cross-Module Residual Learning Towards Lightweight End-to-End Speech Coding.
INTERSPEECH
Kai Zhen, Jongmo Sung, Mi Suk Lee, Seungkwon Beack, Minje Kim
2019 J jnl
Cascaded Cross-Module Residual Learning towards Lightweight End-to-End Speech Coding.
CoRR
Kai Zhen, Jongmo Sung, Mi Suk Lee, Seungkwon Beack, Minje Kim
2018 J jnl
On Psychoacoustically Weighted Cost Functions Towards Resource-Efficient Deep Neural Networks for Speech Denoising.
CoRR
Kai Zhen, Aswin Sivaraman, Jongmo Sung, Minje Kim
2011 Misc conf
G.711.1 Annex D and G.722 Annex B - New ITU-T superwideband codecs.
ICASSP
Lei Miao, Zexin Liu, Chen Hu, Vaclav Eksler, Stéphane Ragot, Claude Lamblin, Balázs Kövesi, Jongmo Sung, Masahiro Fukui, Shigeaki Sasaki, Yusuke Hiwasaki
2009 J jnl
Bandwidth-Scalable Stereo Audio Coding Based on a Layered Structure.
IEICE Trans. Inf. Syst.
Young Han Lee, Deok Su Kim, Hong Kook Kim, Jongmo Sung, Mi Suk Lee, Hyun Joo Bae