Copyright © 2026 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{174606,
        author = {Brahmaji Godi and A.Dillep and V.Laxmana Rao and N.Dhanush Kumar and Ch.Jayaram},
        title = {DEEP LEARNING APPROACH FOR VOICE TO TEXT CONVERSION FOR SOUTH INDIAN LANGUAGES},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {91-96},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174606},
        abstract = {The "Deep Learning Approach for Voice to Text Conversion for South Indian Languages" project aims to develop an advanced system leveraging cutting-edge deep learning techniques to convert spoken South Indian languages into written text. Focusing on languages such as Tamil, Telugu, Kannada and Malayalam, this initiative seeks to harness neural network architectures to accurately transcribe and process regional speech patterns, addressing the linguistic diversity and unique phonetic characteristic soft these languages. By implementing this system, the project intends to enhance accessibility and communication for native speakers, facilitating applications in education, digital interfaces, and professional environments. This work not only addresses the growing demand for localized voice-to-text solutions but also contributes to bridging technological gaps, promoting inclusivity for South Indian language communities.},
        keywords = {Voice to Text Conversion, Natural Language Processing, RNN, Speech Recognition.},
        month = {March},
        }