research
∙
10/17/2022
Sub-8-bit quantization for on-device speech recognition: a regularization-free approach
For on-device automatic speech recognition (ASR), quantization aware tra...
share
research
∙
06/30/2022
Sub-8-Bit Quantization Aware Training for 8-Bit Neural Network Accelerator with On-Device Speech Recognition
We present a novel sub-8-bit quantization-aware training (S8BQAT) scheme...
research
∙
03/27/2021
Scalable and Efficient Neural Speech Coding
This work presents a scalable and efficient neural waveform codec (NWC) ...
research
∙
02/09/2021
Sparsification via Compressed Sensing for Automatic Speech Recognition
In order to achieve high accuracy for machine learning (ML) applications...
research
∙
12/31/2020
Psychoacoustic Calibration of Loss Functions for Efficient End-to-End Neural Audio Coding
Conventional audio coding technologies commonly leverage human perceptio...
research
∙
02/13/2020
Efficient And Scalable Neural Residual Waveform Coding With Collaborative Quantization
Scalability and efficiency are desired in neural speech codecs, which su...
research
∙
08/18/2019
A Dual-Staged Context Aggregation Method Towards Efficient End-To-End Speech Enhancement
In speech enhancement, an end-to-end deep neural network converts a nois...
research
∙
08/18/2019
Efficient Context Aggregation for End-to-End Speech Enhancement Using a Densely Connected Convolutional and Recurrent Network
In speech enhancement, an end-to-end deep neural network converts a nois...
research
∙
06/18/2019
Cascaded Cross-Module Residual Learning towards Lightweight End-to-End Speech Coding
Speech codecs learn compact representations of speech signals to facilit...
research
∙
01/29/2018
On Psychoacoustically Weighted Cost Functions Towards Resource-Efficient Deep Neural Networks for Speech Denoising
We present a psychoacoustically enhanced cost function to balance networ...
research
∙
03/15/2017
