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Statistical Spoken Dialogue Systems and the Challenges for Machine Learning
If you have a question about this talk, please contact Anton Ragni.
This talk will review the principal components of a spoken dialogue system and then discuss the opportunities for applying machine learning for building robust high performance open-domain systems. The talk will be illustrated by recent work at Cambridge University using machine learning for belief tracking, reward estimation, multi-domain policy learning and natural language generation. The talk will conclude by discussing some of the key challenges in scaling these solutions to work in practical systems.
This talk is part of the CUED Speech Group Seminars series.
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