30 citations · 72 across the 5 of their papers we have counts for
5 papers
Scalable and Efficient Neural Speech Coding: A Hybrid Design
Kai Zhen, Jongmo Sung, Mi Suk Lee +2
We present a scalable and efficient neural waveform coding system for speech compression. We formulate the speech coding problem as an autoencoding task, where a convolutional neur…
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…
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…
On Psychoacoustically Weighted Cost Functions Towards Resource-Efficient Deep Neural Networks for Speech Denoising
Kai Zhen, Aswin Sivaraman, Jongmo Sung +1
We present a psychoacoustically enhanced cost function to balance network complexity and perceptual performance of deep neural networks for speech denoising. While training the net…