首页|WhaleLM: Finding Structure and Information in Sperm Whale Vocalizations and Beha vior with Machine Learning
WhaleLM: Finding Structure and Information in Sperm Whale Vocalizations and Beha vior with Machine Learning
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - According to news reporting based on a preprint abstract, our journalists obtained thefollowing quote sourced from bi orxiv.org:“Language models (LMs), which are neural sequence predictors trained to model di stributions overnatural language texts, have come to play a central role in hum an language technologies like machinetranslation and information retrieval. The y have also contributed to the scientific study of human languageitself, enabli ng progress on long-standing questions about the learnability, optimality, and u niversality ofkey features of human languages. Many analogous questions exist i n the study of communication betweennon-human animals—for which, in many case s, we have only a preliminary understanding of signals\ ’structure and use. Can neural sequence models help us understand these animal communication systemsas well? We use these models to characterize the structure and information content of sperm whalevocalizations. Sperm whales (Physeter ma crocephalus) engage in complex, coordinated behaviours likeforaging and navigat ion in the darkness of the ocean while exchanging sequences of rhythmic clicks known as codas.
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