Author(s) :

Alice Chavarot.

Volume/Issue :

Abstract :

Sperm whales (Physeter Macrocephalus) are an endangered species with a highly complex vocalization system. This review summarizes widespread research on how artificial intelligence (AI) can be utilized to examine whether their vocalizations exhibit patterns of meaning compatible with human language. Sperm whales produce highly structured and varying click sequences that prompt debate about the extent of their cognitive and linguistic capacities, but technological and methodological limitations have hindered our efforts to examine these communications at scale. AI, particularly natural language processing within machine learning, enables researchers to identify acoustic patterns, classify call types, and map the complex contextual features of whale communication within their society. This paper evaluates current approaches, namely key researchers and initiatives such as Project CETI (Cetacean Translation Initiative), that apply techniques such as tagging, aerial drones, and tethered buoy arrays to further this research. This review also addresses the critical challenges within the field, namely, limited available datasets, inadequate contextual understanding, and anthropocentric bias. Through the evaluation of both the progress and constraints of AI-led bioacoustics, this paper highlights the potential for interspecies communication and the potential drawbacks it may have, such as specialized fishing and further disruption of sperm whale communities. Ultimately, the goal is not only to investigate the potential linguistic structure of sperm whale vocalizations and explore the possibility of interspecies communication, but also to consider how such findings could influence scientific understanding of animal intelligence, cognition, and human–animal relationships.