Knowledge-Augmented Intelligent Bot Framework for Enabling Accessible Design

Abstract

This paper proposes the development of a WCAG-compliant chatbot capable of generating multimodal content to enhance usability for all users. While LLM-based chatbots excel in generating varied responses, they often struggle with ambiguous or incomplete queries, leading to misaligned outputs. We introduce a framework that formulates domain-specific, persona-driven follow-up questions to clarify ambiguities, utilizing knowledge graphs and human feedback. The system refines queries before generating responses by employing a domain-Specific Multilayer Hierarchical Relational Graph (MHRG) to model user intent. Our preliminary evaluations indicate that the Accessibility Bot improves response relevance and quality as compared to existing techniques.