Paper: A Lightweight and High Performance Monolingual Word Aligner

ACL ID P13-2123
Title A Lightweight and High Performance Monolingual Word Aligner
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2013
Authors

Fast alignment is essential for many nat- ural language tasks. But in the setting of monolingual alignment, previous work has not been able to align more than one sen- tence pair per second. We describe a dis- criminatively trained monolingual word aligner that uses a Conditional Random Field to globally decode the best align- ment with features drawn from source and target sentences. Using just part-of-speech tags and WordNet as external resources, our aligner gives state-of-the-art result, while being an order-of-magnitude faster than the previous best performing system.