Paper: Hypotheses Selection Criteria in a Reranking Framework for Spoken Language Understanding

ACL ID D11-1102
Title Hypotheses Selection Criteria in a Reranking Framework for Spoken Language Understanding
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

Reranking models have been successfully ap- plied to many tasks of Natural Language Pro- cessing. However, there are two aspects of this approach that need a deeper investiga- tion: (i) Assessment of hypotheses generated for reranking at classification phase: baseline models generate a list of hypotheses and these are used for reranking without any assess- ment; (ii) Detection of cases where rerank- ing models provide a worst result: the best hypothesis provided by the reranking model is assumed to be always the best result. In some cases the reranking model provides an incorrect hypothesis while the baseline best hypothesis is correct, especially when base- line models are accurate. In this paper we propose solutions for these two aspects: (i) a semantic inconsistency metric to select pos...