Multilingual Conversation AI for Restaurant Automation

Restaurants are required to respond to menu inquiries, take orders, clarify any customizations, and provide customers with information about the status of their orders all while overseeing the preparation of food and the delivery of in-person service. In times of high demand, the need for multiple customer interactions can overwhelm the staff, lead to longer waiting times, and result in errors when order details are transferred manually. Although digital menus and mobile ordering systems standardise the ordering process, they can force customers to go through fixed menus and forms. This paper outlines the design of a Multilingual Conversational AI for Restaurant Automation system that incorporates both voice and text interaction, multilingual natural language processing (NLP), response generation based on a large language model (LLM), and structured order summarisation. The system takes customer requests via an application or a messaging-oriented interface, converts speech into text where necessary, detects the language and the intent, extracts the food items and the quantities, and uses the restaurant's menu data to produce appropriate contextual responses. A query-summary component converts the conversation into structured order data, containing the names of the items, the quantities, the prices, and the billing information. The architecture is based on a client–server model, with the user interface dealing with the interactions and the backend services handling the AI processing and database operations. The implementation context includes the use of Flutter/Dart, Firebase Authentication, Firebase Firestore, Google Gemini AI, speech-to-text, text-to-speech, and an NLP REST API. The paper covers the motivation, related work, architecture, workflow, the various implementation modules, and an evaluation plan. Since the project materials provided do not include controlled benchmark measurements, no claims are made regarding unsupported accuracy, latency, or cost reduction figures.