How do babies and blind people learn to localise sound without labelled data? We propose that innate mechanisms can provide coarse-grained error signals to boostrap learning. New preprint from @yang-chu.bsky.social. 🤖🧠🧪 arxiv.org/abs/2001.10605
— Dan Goodman (@neuralreckoning.bsky.social) 2025-04-24T16:57:37.637Z
The acoustic cues we use to localise sounds are very specific to each individual, and change through our lifetimes, so we need to be able to learn them. But, most of the time we don't get precise feedback as babies, for blind people, or for sounds outside our visual field. So how do we learn?
— Dan Goodman (@neuralreckoning.bsky.social) 2025-04-24T16:57:37.638Z
Babies have an innate mechanism - the auditory orienting response (AOR) - that lets them turn their head in the left/right direction of the sound. It's not precise, but it means they are born with the ability to tell left from right with at least some accuracy.
— Dan Goodman (@neuralreckoning.bsky.social) 2025-04-24T16:57:37.639Z
We propose that we use this both to kickstart or 'bootstrap' learning a more detailed auditory spatial map, and also to reduce the amount of precise error feedback we need by replacing it with coarse grained feedback.
— Dan Goodman (@neuralreckoning.bsky.social) 2025-04-24T16:57:37.640Z
The mechanism is this: if we hear a sound and turn our heads towards it, our innate mechanism can tell us if we undershot or overshot. Turns out, this gives us enough information to construct an approximate gradient for a neural network to learn by gradient descent.
— Dan Goodman (@neuralreckoning.bsky.social) 2025-04-24T16:57:37.641Z
In our paper we show that in a fairly realistic setting in terms of neural tuning curves, noise, and possible hearing loss, this does indeed let us learn to localise sounds with a tiny number of labels (sometimes zero), including full 3D localisation (front/back, up/down).
— Dan Goodman (@neuralreckoning.bsky.social) 2025-04-24T16:57:37.642Z
We find that there are many different algorithms that let you do this, including reinforcement learning with a noisy innate internal 'reward' (turning your head in the right general direction). We suggest that multiple mechanisms may work together, and individuals may use different strategies.
— Dan Goodman (@neuralreckoning.bsky.social) 2025-04-24T16:57:37.643Z
Our paper gives a framework for further experimental studies, but we can't answer the question of which mechanisms we actually use.
— Dan Goodman (@neuralreckoning.bsky.social) 2025-04-24T16:57:37.644Z
In conclusion: we shouldn't assume that visual feedback is the only way we learn to localise. We're adept at learning in a multitude of ways with surprisingly little signal, and this should inform experimental design. neural-reckoning.org/pub_learning...
— Dan Goodman (@neuralreckoning.bsky.social) 2025-04-24T16:57:37.645Z
Learning spatial hearing via innate mechanisms
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