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@article{174937,
        author = {B. Aditya Bharathi and C.P. Harish Raaj and Jai Harish Satheshkumar and B. Muthusenthil},
        title = {AI Driven Speaker Recognition And Audio Summary Generation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {1221-1224},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174937},
        abstract = {This project harnesses advanced artificial intelligence (AI) and natural language processing (NLP) to develop a comprehensive voice analysis system that generates accurate captions and concise summaries from audio inputs. By analyzing key voice parameters—such as tone, pitch, and modulation—the system effectively captures the nuances of speech. Additionally, speaker diarization is integrated to distinguish between multiple speakers, ensuring precise attribution of dialogue.
The system seamlessly converts spoken content into readable text, enhanced by an advanced summarization algorithm that distills essential information while preserving context. Addressing the growing demand for efficient voice-to-text conversion, this solution proves valuable for transcription services, meeting documentation, and accessibility applications.
A key objective of this project is to deliver a functional prototype capable of handling complex audio inputs, correctly attributing speech, and generating high-quality transcriptions and summaries. With applications across media, legal, and education sectors, this technology offers a powerful tool for managing and interpreting spoken content. By demonstrating how AI and deep learning can revolutionize voice analysis and text generation, this project contributes to making spoken information more accessible, structured, and insightful.},
        keywords = {AI-driven transcription, deep learning, natural language processing, speaker diarization, speech summarization.},
        month = {April},
        }