Rhythm of the Deep: A Computational-Linguistic Test of Duality of Patterning in Sperm Whale Codas
arXiv:2606.16084v1 Announce Type: cross Abstract: Human language has often been described as combining structure at two levels: lower-level units combine into larger units, which then combine into larger sequences. We test for this design feature, duality of patterning, in sperm whale codas using 1,483 codas from the Dominica Sperm Whale Project. Because acoustic similarity can imitate symbolic structure, we treat the problem as computational-linguistic structure discovery from continuous audio rather than as a direct claim about language or meaning. We use a consensus of frozen audio encoders
The increasing sophistication of computational linguistics and audio processing models allows for deeper analysis of complex acoustic structures in nature, enabling researchers to test long-held theories about communication. This particular study leverages advanced AI techniques to explore analogies between animal communication and human language features.
This research contributes to our understanding of the fundamental properties of intelligent communication systems, potentially informing future AI development around emergent linguistic structures and multi-modal understanding. It pushes the boundaries of AI's application in deciphering complex biological data.
The analytical methodology applied to sperm whale codas using advanced computational linguistics shifts how we might approach understanding non-human communication, moving beyond simple correlative observations to structural discoveries. This offers new tools for identifying 'language-like' properties in diverse forms of biological communication.
- · Computational Linguists
- · AI Researchers
- · Marine Biologists
- · Bioacoustics Researchers
Scientific understanding of complex animal communication systems is advanced through novel computational approaches.
New AI models could be developed based on insights from emergent linguistic structures found in animal communication, improving bio-inspired AI.
Long-term, this could contribute to the creation of more sophisticated AI capable of understanding and interacting with non-human intelligence, potentially even facilitating interspecies communication research.
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