7 citations · 31 across the 10 of their papers we have counts for
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cs.CL2018
Improving Robustness of Neural Dialog Systems in a Data-Efficient Way with Turn Dropout
Igor Shalyminov, Sungjin Lee
Neural network-based dialog models often lack robustness to anomalous, out-of-domain (OOD) user input which leads to unexpected dialog behavior and thus considerably limits such mo…
cs.CL2018★ 6 cited
Neural Response Ranking for Social Conversation: A Data-Efficient Approach
Igor Shalyminov, Ondřej Dušek, Oliver Lemon
The overall objective of 'social' dialogue systems is to support engaging, entertaining, and lengthy conversations on a wide variety of topics, including social chit-chat. Apart fr…
cs.CL2018★ 5 cited
Multi-Task Learning for Domain-General Spoken Disfluency Detection in Dialogue Systems
Igor Shalyminov, Arash Eshghi, Oliver Lemon
Spontaneous spoken dialogue is often disfluent, containing pauses, hesitations, self-corrections and false starts. Processing such phenomena is essential in understanding a speaker…