Targeted Help for Spoken Dialogue Systems
Targeted Help for Spoken Dialogue Systems
复制标题
口语对话系统的针对性帮助
DOI：
10.3115/1067807.1067828
复制
发表时间：
2003
期刊：
影响因子：
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通讯作者：
J. Dowding
中科院分区：
文献类型：
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作者：
Beth Ann Hockey;Oliver Lemon;E. Campana;Laura M. Hiatt;Gregory Aist;J. Hieronymus;A. Gruenstein;J. Dowding
我们提出的实验证据表明，提供天真的用户的口语对话系统与即时帮助信息，他们的覆盖范围外的话语提高了他们的成功使用该系统。基于语法的识别器和统计语言模型（SLM）识别器同时运行。如果基于语法的识别器成功，则不使用较不准确的SLM识别器假设。当基于语法的识别器失败并且SLM识别器产生识别假设时，目标帮助代理使用该结果来向用户提供关于识别的内容的反馈、关于话语的问题的诊断以及相关的覆盖范围内示例。覆盖范围内的示例旨在鼓励用户输入与系统的语言模型之间的一致性。我们报告的控制实验上的口头对话系统的命令和控制的模拟机器人直升机。
We present experimental evidence that providing naive users of a spoken dialogue system with immediate help messages related to their out-of-coverage utterances improves their success in using the system. A grammar-based recognizer and a Statistical Language Model (SLM) recognizer are run simultaneously. If the grammar-based recognizer suceeds, the less accurate SLM recognizer hypothesis is not used. When the grammar-based recognizer fails and the SLM recognizer produces a recognition hypothesis, this result is used by the Targeted Help agent to give the user feedback on what was recognized, a diagnosis of what was problematic about the utterance, and a related in-coverage example. The in-coverage example is intended to encourage alignment between user inputs and the language model of the system. We report on controlled experiments on a spoken dialogue system for command and control of a simulated robotic helicopter.