Paper: tucSage: Grammar Rule Induction for Spoken Dialogue Systems via Probabilistic Candidate Selection

ACL ID S14-2119
Title tucSage: Grammar Rule Induction for Spoken Dialogue Systems via Probabilistic Candidate Selection
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

We describe the grammar induction sys- tem for Spoken Dialogue Systems (SDS) submitted to SemEval?14: Task 2. A sta- tistical model is trained with a rich fea- ture set and used for the selection of can- didate rule fragments. Posterior probabil- ities produced by the fragment selection model are fused with estimates of phrase- level similarity based on lexical and con- textual information. Domain and language portability are among the advantages of the proposed system that was experimen- tally validated for three thematically dif- ferent domains in two languages.