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@article{167203,
        author = {SADARAM VIDYA SAGAR and Srinivasu Badugu},
        title = {A literature review on  Interactive Telugu-Language Dialogue System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {3},
        pages = {604-611},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=167203},
        abstract = {In an increasingly interconnected world, the increase in demand for versatile and effective multilingual Natural Language Processing (NLP) systems is being driven. This demand is seen as a significant challenge in regions characterized by rich linguistic diversity, such as Telugu, where NLP applications are currently underrepresented. The endeavour to pioneer an innovative solution addressing this challenge is the focus of this research, with emphasis on the design and development of an interactive Telugu-language dialogue system. This system is equipped with capabilities for keyword extraction, question validation, and multilingual sentiment analysis. Current NLP systems often fall short when applied to low resourced languages like Telugu. The inherent complexities of language, coupled with the limited availability of training data and linguistic resources, pose substantial hurdles. Furthermore, the critical requirement of complete and accurate information for effective dialogue systems remains largely unaddressed. A holistic approach to tackle these challenges is proposed by this research. A novel interactive dialogue system is introduced, specifically designed for the Telugu language, where the integration of advanced keyword extraction and question validation mechanisms ensures that user queries can be effectively understood and processed by the system. Additionally, state-of-the-art Zero-Shot Learning techniques are leveraged to develop a multilingual sentiment analysis module tailored to Telugu language, thereby enhancing the system's capability to comprehend and respond to user sentiment. As an additional innovation, the incorporation of English vocabulary models is explored to improve the overall performance of the Telugu language dialogue system. The aim is to enhance the system's responsiveness, comprehension, and user experience by bridging the linguistic gap between Telugu and English.},
        keywords = {Telugu-Language Text Dialogue System, Natural Language Processing, Tokenization, Part-of-Speech Tagging, Keyword Extraction.},
        month = {August},
        }