VOICE BASED SENTIMENTAL ANALYSIS FOR RESTAURANT REVIEW

Abstract: In the food industry, customer feedback plays a vital role in improving dish quality and service. This project introduces a multilingual feedback system where users can select dishes like idly, dosa, pongal, or vada and provide feedback through text or voice. The system supports multiple languages, including Telugu, Hindi, Tamil, and English, making it accessible to a wide range of users. User feedback is stored in a database and processed using natural language processing (NLP) techniques to classify sentiments as positive or negative. A user-friendly interface ensures easy dish selection and review submission. For administrators, a separate login portal is provided to view, filter, and sort feedback based on dish name and date, helping them monitor customer opinions effectively. By enabling both voice and text input and offering real-time sentiment analysis, the system enhances user engagement and assists food providers in making data-driven improvements. Future extensions may include trend analysis and personalized recommendations based on user feedback patterns.

Keywords: Multilingual Feedback, Sentiment Analysis, Natural Language Processing, Voice and Text Input, Customer Review System