30 citations · 30 across the 2 of their papers we have counts for
4 papers
Psychoacoustic Calibration of Loss Functions for Efficient End-to-End Neural Audio Coding
Kai Zhen, Mi Suk Lee, Jongmo Sung +2
Conventional audio coding technologies commonly leverage human perception of sound, or psychoacoustics, to reduce the bitrate while preserving the perceptual quality of the decoded…
Efficient And Scalable Neural Residual Waveform Coding With Collaborative Quantization
Kai Zhen, Mi Suk Lee, Jongmo Sung +2
Scalability and efficiency are desired in neural speech codecs, which supports a wide range of bitrates for applications on various devices. We propose a collaborative quantization…
A Dual-Staged Context Aggregation Method Towards Efficient End-To-End Speech Enhancement
Kai Zhen, Mi Suk Lee, Minje Kim
In speech enhancement, an end-to-end deep neural network converts a noisy speech signal to a clean speech directly in time domain without time-frequency transformation or mask esti…
Cascaded Cross-Module Residual Learning towards Lightweight End-to-End Speech Coding
Kai Zhen, Jongmo Sung, Mi Suk Lee +2
Speech codecs learn compact representations of speech signals to facilitate data transmission. Many recent deep neural network (DNN) based end-to-end speech codecs achieve low bitr…