Exploring Conversational Language Generation for Rich Content about Hotels
This work addresses the need for better dialogue systems in domains with rich content, such as hotels, but is incremental as it focuses on data collection and analysis without presenting a new generation method.
The paper tackled the problem of generating natural dialogues for hotel information by addressing the mismatch between rich web content and conversational style, quantifying stylistic differences between original descriptions and collected dialogic data.
Dialogue systems for hotel and tourist information have typically simplified the richness of the domain, focusing system utterances on only a few selected attributes such as price, location and type of rooms. However, much more content is typically available for hotels, often as many as 50 distinct instantiated attributes for an individual entity. New methods are needed to use this content to generate natural dialogues for hotel information, and in general for any domain with such rich complex content. We describe three experiments aimed at collecting data that can inform an NLG for hotels dialogues, and show, not surprisingly, that the sentences in the original written hotel descriptions provided on webpages for each hotel are stylistically not a very good match for conversational interaction. We quantify the stylistic features that characterize the differences between the original textual data and the collected dialogic data. We plan to use these in stylistic models for generation, and for scoring retrieved utterances for use in hotel dialogues