The Natural Language Processing group focuses on developing efficient algorithms to process text and to make their information accessible to computer applications. The goal of the group is to design and build software that will analyze, understand, and generate languages that humans use naturally, so that eventually people can address computers as though they were addressing another person.
The challenges our team faces stem from the highly ambiguous nature of natural language. English speakers effortlessly understand a sentence like “Flying planes can be dangerous”. Yet this sentence presents difficulties to a software program because it is ambiguous and relies on real-world knowledge. How much and what sort of context needs to be brought to bear on these questions in order to adequately disambiguate the sentence?
We address these problems using a mix of knowledge-engineered and statistical/machine-learning techniques to disambiguate and respond to natural language input. Our work has implications for applications such as text critiquing, information retrieval, question answering, summarization, gaming, and translation. For example, the grammar checkers in Office for English, French, German, and Spanish are outgrowths of our research.