Linguistic Data

Linguistic data research focuses on developing and utilizing computational methods to analyze and model human language, aiming to improve natural language processing (NLP) tasks and enhance our understanding of language structure and evolution. Current research emphasizes improving data quality through human post-editing of automatically generated data, developing novel methods for cross-modal knowledge transfer (e.g., using Optimal Transport), and creating robust statistical approaches for analyzing diverse and low-resource language datasets. These advancements are crucial for improving machine translation, speech recognition, and other NLP applications, while also providing valuable insights into linguistic theory and the cognitive processes underlying language.