An Interdisciplinary Review and Synthesis of Applied Linguistics in Translation Studies: Bridging Gaps and Advancing Research

Abstract

This study explores the translation gap interconnected by three disciplines: applied linguistics, cognitive linguistics, sociolinguistic adaptation, and artificial intelligence (AI). This aims to address theoretical shortcomings and methodological limitations and build comprehensive models of cross-linguistic translation consistency, accuracy, and cultural adaptation. This study adopts a systematic review of four dimensions: cross-linguistic socio-cognitive discourse mediation, negotiation, AI-assisted translation frameworks, and interdisciplinary conceptual frameworks. It compares models and identification techniques to explore translation methodologies and potentially identify accuracy issues in discourse. The results demonstrate that AI enhances the range of operational possibilities for translation without compromising cultural ideology. However, its discourse is not sufficiently fluid and lacks a complete understanding of the context in some cases. Gaps in pragmatic management, voice bias, and excessive autonomy also highlight the need for human intervention in discourse control and for integrating AI results to achieve greater accuracy in cross-linguistic translation. However, dialogue must be reframed: voice roles must be adjusted to suit the context; more innovative revision processes must be implemented; Develop a coherent policy for regulating ethical content from now on, and continue to develop collaborative human input to ensure its integration. By employing sociolinguistic precision alongside multidisciplinary strategies, adopting progressive support manuals at all levels, and implementing translator training programs, a standard for cultural integration will be strengthened.