30 citations · 76 across the 11 of their papers we have counts for
12 papers
Sub-8-bit quantization for on-device speech recognition: a regularization-free approach
Kai Zhen, Martin Radfar, Hieu Duy Nguyen +3
For on-device automatic speech recognition (ASR), quantization aware training (QAT) is ubiquitous to achieve the trade-off between model predictive performance and efficiency. Amon…
Sub-8-Bit Quantization Aware Training for 8-Bit Neural Network Accelerator with On-Device Speech Recognition
Kai Zhen, Hieu Duy Nguyen, Raviteja Chinta +4
We present a novel sub-8-bit quantization-aware training (S8BQAT) scheme for 8-bit neural network accelerators. Our method is inspired from Lloyd-Max compression theory with practi…
Using Multi-scale SwinTransformer-HTC with Data augmentation in CoNIC Challenge
Chia-Yen Lee, Hsiang-Chin Chien, Ching-Ping Wang +3
Colorectal cancer is one of the most common cancers worldwide, so early pathological examination is very important. However, it is time-consuming and labor-intensive to identify th…
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…
Sparsification via Compressed Sensing for Automatic Speech Recognition
Kai Zhen, Hieu Duy Nguyen, Feng-Ju Chang +3
In order to achieve high accuracy for machine learning (ML) applications, it is essential to employ models with a large number of parameters. Certain applications, such as Automati…
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…