Improving Interaction Quality Estimation with BiLSTMs and the Impact on Dialogue Policy Learning

WS 2019 Stefan Ultes

Learning suitable and well-performing dialogue behaviour in statistical spoken dialogue systems has been in the focus of research for many years. While most work which is based on reinforcement learning employs an objective measure like task success for modelling the reward signal, we use a reward based on user satisfaction estimation... (read more)

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