Advancing Translation Quality Assessment: Integrating AI Models for Real-time Feedback

Abstract

With the use of AI models for real-time reception a feedback, this review attempts to show how the assessment of the quality of translation is changing. The investigation covers aspects such as the technical side of the integration, efficiency and minimization of human errors, influence upon the translation industry including its services, costs and competitiveness and so forth. User experience and feedback, ethical issues, and implementation barriers are addressed for a more holistic view of the impacts of AI translation assessment. The discussion goes further and addresses the future of it, the possible wide uptake of it, the features to be expected and the difficulties to be faced by the industry. The summary, however, shows that there is a positive change in practice where the AI will be merged within the translation assessment criteria, the barriers will be lifted and this will surely lead to modern and unprecedented standards in translation in a hair-cutting edge of language services provided through the combination of human experts and AI techniques.