Context-Aware Semantic Ambiguity Resolution in Cross-Cultural Dialogue Understanding

Abstract

Cross-cultural dialogue systems face significant challenges in semantic ambiguity resolution due to varying cultural contexts and linguistic nuances. This paper presents a novel context-aware framework for semantic ambiguity resolution in cross-cultural dialogue understanding. Our approach integrates cultural context modeling with multi-level ambiguity resolution algorithms to enhance dialogue comprehension accuracy across diverse cultural backgrounds. The proposed framework employs hierarchical semantic representation structures that capture both linguistic and cultural dependencies. Experimental evaluation on multi-cultural dialogue datasets demonstrates substantial improvements in ambiguity resolution accuracy, achieving 23.7% enhancement over baseline approaches. The framework successfully identifies and resolves cultural-specific semantic ambiguities while maintaining contextual coherence throughout multi-turn conversations. Results indicate significant performance gains in cross-cultural communication scenarios, particularly in handling implicit cultural references and context-dependent interpretations. The methodology provides valuable insights for developing culturally-aware dialogue systems that can effectively navigate semantic complexities arising from intercultural interactions while maintaining computational efficiency and practical deployment feasibility.