LUNA口语对话系统:超越话语分类

Marco Dinarelli, Evgeny A. Stepanov, S. Varges, G. Riccardi
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引用次数: 12

摘要

我们提出了一个用于复杂问题解决任务的呼叫路由应用程序。目前的呼叫路由研究主要是针对呼叫类型的分类。在本文中,我们进一步研究了呼叫路由:初始呼叫分类与鲁棒统计口语理解模块并行完成。接下来是一个对话,在传递调用之前从用户那里获得更多与任务相关的细节。对话功能还允许我们获得对初始分类器猜测的澄清。在评估的基础上,我们证明了单独基于呼叫分类进行对话可以显著改善呼叫路由。我们根据对真实用户的标准度量给出了系统的主观和客观评价结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The LUNA Spoken Dialogue System: Beyond utterance classification
We present a call routing application for complex problem solving tasks. Up to date work on call routing has been mainly dealing with call-type classification. In this paper we take call routing further: Initial call classification is done in parallel with a robust statistical Spoken Language Understanding module. This is followed by a dialogue to elicit further task-relevant details from the user before passing on the call. The dialogue capability also allows us to obtain clarifications of the initial classifier guess. Based on an evaluation, we show that conducting a dialogue significantly improves upon call routing based on call classification alone. We present both subjective and objective evaluation results of the system according to standard metrics on real users.
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