New publication: Approaching an unknown communication system

We have a pre-print out based on our work with Project CETI, an initiative to decipher sperm whale communication using machine learning.

In the paper, we combine approaches that help discover how known properties of human language are learned by generative models when trained on labeled speech audio data with methodology inspired by causal inference and apply it to the communication system of sperm whales, for which we do not have any such ground truth. With this, we can propose what components of their communication might serve as the carriers of meaning, not only giving credence to existing theories but also suggesting additional ways the whales might encode information.