Paper: Generation by Inverting a Semantic Parser that Uses Statistical Machine Translation

ACL ID N07-1022
Title Generation by Inverting a Semantic Parser that Uses Statistical Machine Translation
Venue Human Language Technologies
Session Main Conference
Year 2007
Authors

This paper explores the use of statisti- cal machine translation (SMT) methods for tactical natural language generation. We present results on using phrase-based SMT for learning to map meaning repre- sentations to natural language. Improved results are obtained by inverting a seman- tic parser that uses SMT methods to map sentences into meaning representations. Finally, we show that hybridizing these two approaches results in still more accu- rate generation systems. Automatic and human evaluation of generated sentences arepresentedacrosstwodomainsandfour languages.