Language Representation

Language representation research focuses on creating effective computational models of language that capture its nuances and complexities for various applications. Current efforts concentrate on improving multilingual capabilities, particularly for low-resource languages, often using transformer-based architectures and incorporating information like language and script embeddings to enhance representation learning. These advancements are significant because they enable improved performance in numerous natural language processing tasks, including machine translation, text-to-speech synthesis, and cross-lingual information retrieval, and have implications for broader AI applications like robotics and recommendation systems.