Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{174636,
        author = {Lav Dixit and Garima Yadav and Sakshi Thakur and Divakar Tyagi and Adarsh Pal},
        title = {ANALYSIS OF SPERM WHALE COMMUNICATION: A REVIEW PAPER},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {205-208},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174636},
        abstract = {Sperm Whales (Physeter macrocephalus) are extremely social marine that communicate using codas – discrete order of broadband clicks.[5] They generate a complicated vocal system that remains largely unexplored. Long – established methods of examine whale vocalizations have need of extensive manual transcription, place a limit on progress. Although, the latest advancements in Artificial Intelligence, Machine Learning have recognize this field by authorize automated detection, classification, and interpretation of whale sounds.[2,4] This review integrates key Artificial Intelligence – driven techniques, which includes Deep Learning, Natural Language Processing, Graph – based Clustering, and Spectral Analysis, to decrypt whale communication patterns.[2,4] In addition, it inspect the prospective combinatorial nature of sperm whale vocalizations, their contextual variations, and their analogous with human language configuration.[5] The study further highlights the ethical implications of Artificial Intelligence – driven whale communication research, confirm that similar technologies remain unintrusive and preservation – focused. This study contributes to Project CETI (Cetacean Translation Initiative) By recognizing existing gap and propose future research directions, this review be conductive to the comprehensive goal of deciphering sperm whale communication, facilitate Artificial Intelligence applications in bioacoustics,[2] and contribute to marine conservation efforts. [3,8]},
        keywords = {Sperm Whales (Physeter macrocephalus),[5] Codas, Broadband Clicks, Vocal Communication, Complex Vocal System, Manual Transcription, Artificial Intelligence (AI),[3] Machine Learning (ML), Automated Detection, Classification, Interpretation, Deep Learning,[3] Natural Language Processing (NLP), Graph – Based Clustering, Spectral Analysis, Combinatorial Nature, Contextual Variations, Human Language Similarities, Ethical Implications,[3] Unintrusive Technology, Preservation – Focused Research, Project CETI (Cetacean Translation Initiative),[4,8] Bioacoustics, Marine Conservation, Future Research Directions,[4] Deciphering Whale Communication.},
        month = {March},
        }