Generation by Inverting a Semantic Parser that Uses Statistical Machine Translation
Yuk Wah Wong, Raymond J. Mooney · 2007
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 are presented across two domains and four languages. 1