SAIL-GRS: Grammar Induction for Spoken Dialogue Systems using CF-IRF Rule Similarity

The SAIL-GRS system is based on a widely used approach originating from information retrieval and document indexing, the TF -IDF measure. In this implementation for spoken dialogue system grammar induction, rule constituent frequency (CF ) and inverse rule frequency (IRF ) measures are used for estimating lexical and semantic similarity of candidate grammar rules to a seed set of rule pattern instances. The performance of the system is evaluated for the English language in three different domains, travel, tourism and finance and in the travel domain, for Greek. The simplicity of our approach makes it quite easy and fast to implement irrespective of language and domain. The results show that the SAILGRS system performs quite well in all three domains and in both languages.