首页> 外文期刊>Computer speech and language >Empirical feature analysis for dialogue breakdown detection
【24h】

Empirical feature analysis for dialogue breakdown detection

机译:对话故障检测的经验特征分析

获取原文
获取原文并翻译 | 示例

摘要

Chat-oriented dialogue systems sometimes generate inappropriate response utterances to user utterances that cause dialogue breakdown. Detecting such inappropriate utterances and suppressing them will support the continuation of the dialogue. Although a previous state-of-the-art dialogue breakdown detector leveraged dialogue-act transitions and word-based similarities between utterance pairs, these features are insufficient to evaluate the appropriateness of question-answering or relatedness between utterances that share few topic words. In this paper, we propose novel features to assess these problems, and examine their effectiveness for improving the performance of dialogue breakdown detection. (C) 2018 Elsevier Ltd. All rights reserved.
机译:面向聊天的对话系统有时会对导致对话中断的用户话语生成不适当的响应话语。检测到这种不适当的话语并加以制止将有助于继续对话。尽管以前的最新对话故障检测器利用对话对之间的转换以及话语对之间基于单词的相似性,但是这些功能不足以评估共享少量主题词的话语之间的问题回答或相关性的适当性。在本文中,我们提出了新颖的功能来评估这些问题,并检查它们对提高对话故障检测性能的有效性。 (C)2018 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号