Low Resource Neural Machine Translation

Low Resource Neural Machine Translation (LRNMT) is an important research direction in the field of natural language processing, aiming to enhance the automatic translation capabilities for data-scarce languages through deep learning technologies. The goal of this technology is to optimize neural network models and improve translation quality and efficiency under conditions where training data is limited, thereby enabling effective cross-lingual information exchange and dissemination. Its application value lies in expanding the language coverage of machine translation systems, promoting information sharing and cultural exchange in multilingual environments.