25 citations · 64 across the 7 of their papers we have counts for
7 papers
CCATMos: Convolutional Context-aware Transformer Network for Non-intrusive Speech Quality Assessment
Yuchen Liu, Li-Chia Yang, Alex Pawlicki +1
Speech quality assessment has been a critical component in many voice communication related applications such as telephony and online conferencing. Traditional intrusive speech qua…
CalFAT: Calibrated Federated Adversarial Training with Label Skewness
Chen Chen, Yuchen Liu, Xingjun Ma +1
Recent studies have shown that, like traditional machine learning, federated learning (FL) is also vulnerable to adversarial attacks. To improve the adversarial robustness of FL, f…
Class-Discriminative CNN Compression
Yuchen Liu, David Wentzlaff, S. Y. Kung
Compressing convolutional neural networks (CNNs) by pruning and distillation has received ever-increasing focus in the community. In particular, designing a class-discrimination ba…
Evolving Transferable Neural Pruning Functions
Yuchen Liu, S. Y. Kung, David Wentzlaff
Structural design of neural networks is crucial for the success of deep learning. While most prior works in evolutionary learning aim at directly searching the structure of a netwo…
Rethinking Class-Discrimination Based CNN Channel Pruning
Yuchen Liu, David Wentzlaff, S. Y. Kung
Channel pruning has received ever-increasing focus on network compression. In particular, class-discrimination based channel pruning has made major headway, as it fits seamlessly w…
Synchronous Speech Recognition and Speech-to-Text Translation with Interactive Decoding
Yuchen Liu, Jiajun Zhang, Hao Xiong +5
Speech-to-text translation (ST), which translates source language speech into target language text, has attracted intensive attention in recent years. Compared to the traditional p…