Deep Neural Networks Show Promise As Models Of Human Hearing

In a new study from MIT, researchers have found that deep neural networks trained to perform auditory tasks generate internal representations that share properties of representations seen in the human brain when people are listening to the same sounds. The study also provides insight into how to best train this type of model, suggesting that models trained on auditory input including background noise more closely mimic the activation patterns of the human auditory cortex.