Jongmo Sung

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 15

Top Topics

Quantization Noise

Top Venues

IEEE Signal Process. Lett.

Publications

Seungmin Shin, Joon Byun, Jongmo Sung, Seungkwon Beack, Youngcheol Park
Quantization Noise Masking in Perceptual Neural Audio Coder. ICASSP (2024)
Joon Byun, Seungmin Shin, Jongmo Sung, Seungkwon Beack, Youngcheol Park
Perceptual Improvement of Deep Neural Network (DNN) Speech Coder Using Parametric and Non-parametric Density Models. INTERSPEECH (2023)
Joon Byun, Seungmin Shin, Youngcheol Park, Jongmo Sung, Seungkwon Beack
A Perceptual Neural Audio Coder with a Mean-Scale Hyperprior. ICASSP (2023)
Seungmin Shin, Joon Byun, Youngcheol Park, Jongmo Sung, Seungkwon Beack
Deep Neural Network (DNN) Audio Coder Using A Perceptually Improved Training Method. ICASSP (2022)
Joon Byun, Seungmin Shin, Jongmo Sung, Seungkwon Beack, Youngcheol Park
Optimization of Deep Neural Network (DNN) Speech Coder Using a Multi Time Scale Perceptual Loss Function. INTERSPEECH (2022)
Kai Zhen, Jongmo Sung, Mi Suk Lee, Seungkwon Beack, Minje Kim
Scalable and Efficient Neural Speech Coding: A Hybrid Design. IEEE ACM Trans. Audio Speech Lang. Process. 30 (2022)
Joon Byun, Seungmin Shin, Youngcheol Park, Jongmo Sung, Seungkwon Beack
Development of a Psychoacoustic Loss Function for the Deep Neural Network (DNN)-Based Speech Coder. Interspeech (2021)
Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, Minje Kim
Psychoacoustic Calibration of Loss Functions for Efficient End-to-End Neural Audio Coding. CoRR (2021)
Kai Zhen, Jongmo Sung, Mi Suk Lee, Seungkwon Beack, Minje Kim
Scalable and Efficient Neural Speech Coding. CoRR (2021)
Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, Minje Kim
Efficient And Scalable Neural Residual Waveform Coding With Collaborative Quantization. CoRR (2020)
Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, Minje Kim
Efficient and Scalable Neural Residual Waveform Coding with Collaborative Quantization. ICASSP (2020)
Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, Minje Kim
Psychoacoustic Calibration of Loss Functions for Efficient End-to-End Neural Audio Coding. IEEE Signal Process. Lett. 27 (2020)
Kai Zhen, Jongmo Sung, Mi Suk Lee, Seungkwon Beack, Minje Kim
Cascaded Cross-Module Residual Learning Towards Lightweight End-to-End Speech Coding. INTERSPEECH (2019)
Kai Zhen, Jongmo Sung, Mi Suk Lee, Seungkwon Beack, Minje Kim
Cascaded Cross-Module Residual Learning towards Lightweight End-to-End Speech Coding. CoRR (2019)
Kai Zhen, Aswin Sivaraman, Jongmo Sung, Minje Kim
On Psychoacoustically Weighted Cost Functions Towards Resource-Efficient Deep Neural Networks for Speech Denoising. CoRR (2018)
Lei Miao, Zexin Liu, Chen Hu, Vaclav Eksler, Stéphane Ragot, Claude Lamblin, Balázs Kövesi, Jongmo Sung, Masahiro Fukui, Shigeaki Sasaki, Yusuke Hiwasaki
G.711.1 Annex D and G.722 Annex B - New ITU-T superwideband codecs. ICASSP (2011)
Young Han Lee, Deok Su Kim, Hong Kook Kim, Jongmo Sung, Mi Suk Lee, Hyun Joo Bae
Bandwidth-Scalable Stereo Audio Coding Based on a Layered Structure. IEICE Trans. Inf. Syst. (12) (2009)