The Role of Binary Language in Building AI-Powered Translation and Dubbing Terminology Dictionaries

The integration of binary language encoding in artificial intelligence (AI) systems has significantly advanced the development of specialized translation and dubbing terminology dictionaries. Binary encoding provides a compact, precise, and efficient method for representing linguistic data, which facilitates enhanced processing speed and accuracy in AI-powered translation tools. This study investigates the role of binary language in building translation and dubbing terminology dictionaries, focusing on the challenges posed by audiovisual localization and domain-specific terminologies. By reviewing recent literature both within Iran and internationally, we contextualize current advancements in binary lexicon design and AI translation integration. Utilizing a curated corpus of dubbing terminology sourced from specialized journals and interviews with prominent Iranian dubbing experts, we developed a binary-encoded dictionary framework. The evaluation against traditional string-based dictionaries demonstrates improved retrieval speed, precision, and recall, particularly in English-to-Persian and French-to-Persian language pairs. Our results highlight the potential of binary encoding to enhance term alignment and consistency in dubbing workflows, which is critical for maintaining lip-sync and cultural fidelity. This paper contributes to the growing field of AI-assisted audiovisual translation by presenting a novel lexicographic methodology that bridges computational efficiency with linguistic complexity.

کلیدواژه ها:

AI Translation ، Audiovisual Localization ، Binary Encoding ، Dubbing Terminology ، Lexicographic Framework