4 citations · 7 across the 4 of their papers we have counts for
4 papers
Learning from Real Stuttering: Synthetic Mandarin Stuttering Speech for Data Augmentation in Speech Recognition
Yao Lu, Jiaming Zhou, Zhongyuan Fu +1
Mandarin stuttered speech remains under-resourced, limiting the development of robust speech processing systems. We present a Mandarin stuttering speech synthesis and data augmenta…
SepPrune: Structured Pruning for Efficient Deep Speech Separation
Yuqi Li, Kai Li, Xin Yin +6
Although deep learning has substantially advanced speech separation in recent years, most existing studies continue to prioritize separation quality while overlooking computational…
SGLP: A Similarity Guided Fast Layer Partition Pruning for Compressing Large Deep Models
Yuqi Li, Yao Lu, Junhao Dong +7
Layer pruning has emerged as a potent approach to remove redundant layers in the pre-trained network on the purpose of reducing network size and improve computational efficiency. H…
Scaling Up Quantization-Aware Neural Architecture Search for Efficient Deep Learning on the Edge
Yao Lu, Hiram Rayo Torres Rodriguez, Sebastian Vogel +2
Neural Architecture Search (NAS) has become the de-facto approach for designing accurate and efficient networks for edge devices. Since models are typically quantized for edge depl…