Evaluating Spoken Dialogue Processing for Time-Offset Interaction
Evaluating Spoken Dialogue Processing for Time-Offset Interaction
复制标题
评估时间偏移交互的口语对话处理
DOI：
10.18653/v1/w15-4629
复制
发表时间：
2015
期刊：
影响因子：
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通讯作者：
Anton Leuski
中科院分区：
文献类型：
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作者：
D. Traum;Kallirroi Georgila;Ron Artstein;Anton Leuski
本文介绍了第一次评估的全自动原型系统的时间偏移的互动，也就是说，一个活生生的人和录音的人谁是不是临时共同出席之间的对话。语音识别的单词错误率在通用语言模型中低至5%，在特定领域模型中低至19%，语言理解可以识别60 - 66%的用户话语的适当直接响应，同时将错误保持在10 - 16%（其余为间接或偏离主题的响应）。这足以使对话自然流畅，相对开放，并收集了不到2000份录音发言。
This paper presents the first evaluation of a full automated prototype system for time-offset interaction, that is, conversation between a live person and recordings of someone who is not temporally copresent. Speech recognition reaches word error rates as low as 5% with generalpurpose language models and 19% with domain-specific models, and language understanding can identify appropriate direct responses to 60‐66% of user utterances while keeping errors to 10‐16% (the remainder being indirect, or off-topic responses). This is sufficient to enable a natural flow and relatively open-ended conversations, with a collection of under 2000 recorded statements.