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@article{198168,
        author = {Dharani R and Akilesh J and Kamalesh V and Guru Prasad S},
        title = {Meta Vision},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {13894-13898},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198168},
        abstract = {In the evolving hospitality industry, enhancing customer experience while maintaining operational efficiency has become a critical priority. Traditional food ordering systems in hotels and restaurants often depend on manual interaction, such as phone calls, waitstaff communication, or mobile text input, which can lead to delays, miscommunication, and order inaccuracies. To address these challenges, this project introduces MetaVisionn, an AI-powered voice-based smart ordering system.
MetaVisionn enables customers to place food orders using natural speech through their mobile devices, eliminating the need for typing or manual input. The system utilizes advanced Speech-to-Text technology to convert spoken language into text in real time, followed by Natural Language Processing (NLP) techniques to extract key order details such as food items, quantities, special instructions, and delivery location (room or table number). The processed data is then structured and transmitted to hotel dashboards and kitchen display systems.
A unique aspect of MetaVisionn is its ability to present both the original spoken transcript and the AI-interpreted order, ensuring transparency and reducing errors in communication. The system also incorporates real-time streaming of spoken words, enhancing user interaction and engagement. By integrating AI-driven automation with intuitive voice interfaces, MetaVisionn significantly improves service speed, accuracy, and overall customer satisfaction, making it a scalable solution for modern smart hospitality environments.},
        keywords = {},
        month = {April},
        }