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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

ArXiv
IEEE Sigport