Projects | Text Analysis

Deep learning architectures handle various natural language processing tasks, including parsing, part-of-speech tagging, chunking, named-entity recognition and semantic role labeling. Instead of depending on hand-crafted features that are engineered for specific tasks, the system we have developed learns internal representations from mostly unlabeled training data. This makes the system very flexible, since it can be trained for a different language simply by training with text data from that language. So far we have developed systems for English, Japanese and Chinese, achieving state-of-the-art or better performance in all cases.