Best Student Paper Award on AES for the Masters’ Thesis work of Guanxin Jiang
The paper “InSE-NET: A Perceptually Coded Audio Quality Model based on CNN” shows that it is possible to mimic a state-of-the-art coded audio quality metric with deep neural networks, followed by improving over it – completely with programmatically generated data.
Congratulations Guaxin and our colleagues at Dolby for their great success!
View the paper on