Multimodal Machine Translation

Multimodal Machine Translation is a subtask in the field of Natural Language Processing, aimed at utilizing multiple data sources for machine translation, such as the combination of text and images, to improve the accuracy and context relevance of translations. By integrating multimodal information, this task can better understand the content of the source language and generate more accurate target language expressions, making it highly valuable for various applications.