Translation Memory

Translation memory (TM) systems store and reuse previously translated segments to improve efficiency and consistency in machine translation (MT). Current research focuses on enhancing TM integration with neural MT models, particularly leveraging deep learning techniques like transformers and GANs to improve retrieval, fuzzy matching, and the generation of high-quality synthetic data for low-resource languages. These advancements aim to optimize TM utilization within computer-aided translation (CAT) tools, leading to faster, more accurate, and cost-effective translation workflows for both professional translators and MT systems.