| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 384414 | Expert Systems with Applications | 2012 | 8 Pages |
The process of Natural Language Generation for a Conversational Agent translates some semantic language to its surface form expressed in natural language. In this paper, we are going to show a Case Based Reasoning technique which is easily extensible and adaptable to multiple domains and languages, that generates coherent phrases and produces a natural outcome in the context of a Conversational Agent that maintains a dialogue with the user.
► We propose a Case Based Reasoning (CBR) method for Natural Language Generation (NLG) in dialogs. ► Grammar and symbolic approaches to NLG have a closed style unuseful for dialogs. ► Symbolic approaches to NLG requires expert knowledge that is expensive to gather. ► The CBR-NLG uses speech acts and templates to get credible and realistic language. ► The CBR-NLG is useful in several languages and domains without expert knowledge.
