Making Grammar-Based Generation Easier to Deploy in Dialogue Systems
Making Grammar-Based Generation Easier to Deploy in Dialogue Systems
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DOI：
10.3115/1622064.1622102
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发表时间：
2008-06
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影响因子：
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通讯作者：
David DeVault;D. Traum;Ron Artstein
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文献类型：
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作者：
David DeVault;D. Traum;Ron Artstein
我们提出了一个开发管道和相关的算法，旨在使基于语法的生成更容易部署在实现的对话系统。我们的方法实现了一个实际的权衡系统的生成组件的能力和创作和维护的负担上一代内容作者部署的系统。为了评估我们的方法，我们进行了一个人类的评级研究与系统建设者谁的工作在一个共同的大规模口语对话系统。我们的研究结果证明了我们的方法的可行性，并说明了手工创作的文本，我们的基于语法的方法，和竞争浅统计NLG技术之间的创作/性能权衡。
We present a development pipeline and associated algorithms designed to make grammarbased generation easier to deploy in implemented dialogue systems. Our approach realizes a practical trade-off between the capabilities of a system's generation component and the authoring and maintenance burdens imposed on the generation content author for a deployed system. To evaluate our approach, we performed a human rating study with system builders who work on a common largescale spoken dialogue system. Our results demonstrate the viability of our approach and illustrate authoring/performance trade-offs between hand-authored text, our grammar-based approach, and a competing shallow statistical NLG technique.