OpinionConv: Conversational Product Search with Grounded Opinions
August 08, 2023 Β· Declared Dead Β· π SIGDIAL Conferences
"No code URL or promise found in abstract"
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Authors
Vahid Sadiri Javadi, Martin Potthast, Lucie Flek
arXiv ID
2308.04226
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CL,
cs.IR,
cs.LG
Citations
7
Venue
SIGDIAL Conferences
Last Checked
4 months ago
Abstract
When searching for products, the opinions of others play an important role in making informed decisions. Subjective experiences about a product can be a valuable source of information. This is also true in sales conversations, where a customer and a sales assistant exchange facts and opinions about products. However, training an AI for such conversations is complicated by the fact that language models do not possess authentic opinions for their lack of real-world experience. We address this problem by leveraging product reviews as a rich source of product opinions to ground conversational AI in true subjective narratives. With OpinionConv, we develop the first conversational AI for simulating sales conversations. To validate the generated conversations, we conduct several user studies showing that the generated opinions are perceived as realistic. Our assessors also confirm the importance of opinions as an informative basis for decision-making.
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