Irresponsible Hype from MIT Technology Review
MIT Technology Review is running a story claiming that a group of machine learning researchers used a convolutional deep learning neural network to solve the cocktail party problem. Don't you believe it. The network that was used has to be pre-trained separately on individual vocals and musical instruments in order to separate out the vocals from the background music. In other words, it can only separate voice from music.
The human brain needs no such training. We can instantly latch on to any voice or sound, even one that we had never heard before, while ignoring all others. We have no trouble focusing on a strange voice speaking a foreign language in a room full of talking people, with or without music playing. This is what the true cocktail party problem is about. A deep learning network cannot pay attention to an arbitrary voice while ignoring the others. To do this, it would have to be pre-trained on all the voices individually.
Note: I posted a protest comment at the end of the article but MIT Tech Review editors chose to censor it. I guess it is easier to attract visitors with a lie than the truth.
It Is Not about Speech
Contrary to rumors, the cocktail party problem has nothing specifically to do with speech or sounds. To focus on individual sounds, the brain uses the same mechanism that it normally uses to pay attention to anything, be it a bird, the letters and words on the computer screen or grandma's voice. The attention mechanism of the brain is universal and is an inherent part of the architecture of memory and how objects are represented in it. Unlike deep learning neural networks, it does not have to be trained separately for every sound or object. The ability of the cortex to instantly model a novel visual or auditory object is a major part of the brain's attention mechanism.
It is clear that the auditory cortex can quickly model a new sound on the fly and tune its attention mechanism to it. No deep learning network can do that. And knowing what I know about how the brain's attention mechanism works, I can confidently say that no deep learning network can ever do that.
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