Paper: Deep Learning for Chinese Word Segmentation and POS Tagging

ACL ID D13-1061
Title Deep Learning for Chinese Word Segmentation and POS Tagging
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

This study explores the feasibility of perform- ing Chinese word segmentation (CWS) and POS tagging by deep learning. We try to avoid task-specific feature engineering, and use deep layers of neural networks to discover relevant features to the tasks. We leverage large-scale unlabeled data to improve internal representa- tion of Chinese characters, and use these im- proved representations to enhance supervised word segmentation and POS tagging models. Our networks achieved close to state-of-the- art performance with minimal computational cost. We also describe a perceptron-style al- gorithm for training the neural networks, as an alternative to maximum-likelihood method, to speed up the training process and make the learning algorithm easier to be implemented.