Ruuh: A Deep Learning Based Conversational Social Agent
October 22, 2018 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Sonam Damani, Nitya Raviprakash, Umang Gupta, Ankush Chatterjee, Meghana Joshi, Khyatti Gupta, Kedhar Nath Narahari, Puneet Agrawal, Manoj Kumar Chinnakotla, Sneha Magapu, Abhishek Mathur
arXiv ID
1810.12097
Category
cs.CL: Computation & Language
Citations
6
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Dialogue systems and conversational agents are becoming increasingly popular in the modern society but building an agent capable of holding intelligent conversation with its users is a challenging problem for artificial intelligence. In this demo, we demonstrate a deep learning based conversational social agent called "Ruuh" (facebook.com/Ruuh) designed by a team at Microsoft India to converse on a wide range of topics. Ruuh needs to think beyond the utilitarian notion of merely generating "relevant" responses and meet a wider range of user social needs, like expressing happiness when user's favorite team wins, sharing a cute comment on showing the pictures of the user's pet and so on. The agent also needs to detect and respond to abusive language, sensitive topics and trolling behavior of the users. Many of these problems pose significant research challenges which will be demonstrated in our demo. Our agent has interacted with over 2 million real world users till date which has generated over 150 million user conversations.
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