3 citations · 3 across the 2 of their papers we have counts for
4 papers
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…
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…