159 citations · 176 across the 6 of their papers we have counts for
8 papers
Longitudinal Data and a Semantic Similarity Reward for Chest X-Ray Report Generation
Aaron Nicolson, Jason Dowling, Bevan Koopman
Radiologists face high burnout rates, partially due to the increasing volume of Chest X-rays (CXRs) requiring interpretation and reporting. Automated CXR report generation holds pr…
Improving Chest X-Ray Report Generation by Leveraging Warm Starting
Aaron Nicolson, Jason Dowling, Bevan Koopman
Automatically generating a report from a patient's Chest X-Rays (CXRs) is a promising solution to reducing clinical workload and improving patient care. However, current CXR report…
Time-Frequency Attention for Monaural Speech Enhancement
Qiquan Zhang, Qi Song, Zhaoheng Ni +2
Most studies on speech enhancement generally don't consider the energy distribution of speech in time-frequency (T-F) representation, which is important for accurate prediction of…
Deep Learning-Based Single-Ended Objective Quality Measures for Time-Scale Modified Audio
Timothy Roberts, Aaron Nicolson, Kuldip K. Paliwal
Objective evaluation of audio processed with Time-Scale Modification (TSM) is seeing a resurgence of interest. Recently, a labelled time-scaled audio dataset was used to train an o…
Deep Residual-Dense Lattice Network for Speech Enhancement
Mohammad Nikzad, Aaron Nicolson, Yongsheng Gao +3
Convolutional neural networks (CNNs) with residual links (ResNets) and causal dilated convolutional units have been the network of choice for deep learning approaches to speech enh…
Monaural Speech Enhancement Using a Multi-Branch Temporal Convolutional Network
Qiquan Zhang, Aaron Nicolson, Mingjiang Wang +2
Deep learning has achieved substantial improvement on single-channel speech enhancement tasks. However, the performance of multi-layer perceptions (MLPs)-based methods is limited b…