170 citations · 804 across the 22 of their papers we have counts for
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cs.LG2015★ 24 cited
Reward Shaping with Recurrent Neural Networks for Speeding up On-Line Policy Learning in Spoken Dialogue Systems
Pei-Hao Su, David Vandyke, Milica Gasic +3
Statistical spoken dialogue systems have the attractive property of being able to be optimised from data via interactions with real users. However in the reinforcement learning par…
cs.LG2015★ 51 cited
Learning from Real Users: Rating Dialogue Success with Neural Networks for Reinforcement Learning in Spoken Dialogue Systems
Pei-Hao Su, David Vandyke, Milica Gasic +4
To train a statistical spoken dialogue system (SDS) it is essential that an accurate method for measuring task success is available. To date training has relied on presenting a tas…