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Found 6 papers, 5 papers with code
Deep learning for minimum mean-square error approaches to speech enhancement
MMSE approaches utilising the proposed a priori SNR estimator are able to achieve higher enhanced speech quality and intelligibility scores than recent masking- and mapping-based deep learning approaches.
Monaural Speech Enhancement Using a Multi-Branch Temporal Convolutional Network
Deep learning has achieved substantial improvement on single-channel speech enhancement tasks.
Deep Residual-Dense Lattice Network for Speech Enhancement
Motivated by this, we propose the residual-dense lattice network (RDL-Net), which is a new CNN for speech enhancement that employs both residual and dense aggregations without over-allocating parameters for feature re-usage.
Ranked #16 on
Speech Enhancement
on VoiceBank + DEMAND
Deep Learning-Based Single-Ended Objective Quality Measures for Time-Scale Modified Audio
This DE measure was an extension of Perceptual Evaluation of Audio Quality, and required reference and test signals.
Improving Chest X-Ray Report Generation by Leveraging Warm Starting
Our experimental investigation demonstrates that the Convolutional vision Transformer (CvT) ImageNet-21K and the Distilled Generative Pre-trained Transformer 2 (DistilGPT2) checkpoints are best for warm starting the encoder and decoder, respectively.
Longitudinal Data and a Semantic Similarity Reward for Chest X-Ray Report Generation
To improve diagnostic accuracy, we propose a CXR report generator that integrates aspects of the radiologist workflow and is trained with our proposed reward for reinforcement learning.
