统计口语对话系统和机器学习的挑战

S. Young
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引用次数: 4

摘要

本讲座将回顾口语对话系统的主要组成部分,然后讨论应用机器学习构建健壮的高性能开放域系统的机会。这次演讲将通过剑桥大学最近的工作来说明,该工作将机器学习用于信念跟踪、奖励估计、多领域策略学习和自然语言生成。讲座最后将讨论将这些解决方案扩展到实际系统中的一些关键挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical Spoken Dialogue Systems and the Challenges for Machine Learning
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.
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