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首页> 外文期刊>International journal of speech technology >Effects of Speech Recognition Accuracy on the Performance of DARPA Communicator Spoken Dialogue Systems
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Effects of Speech Recognition Accuracy on the Performance of DARPA Communicator Spoken Dialogue Systems

机译:语音识别精度对DARPA Communicator口语对话系统性能的影响

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The DARPA Communicator program explored ways to construct better spoken-dialogue systems, with which users interact via speech alone to perform relatively complex tasks such as travel planning. During 2000 and 2001 two large data sets were collected from sessions in which paid users did travel planning using the Communicator systems that had been built by eight research groups. The research groups improved their systems intensively during the ten months between the two data collections. In this paper, we analyze these data sets to estimate the effects of speech recognition accuracy, as measured by Word Error Rate (WER), on other metrics. The effects that we found were linear. We found correlation between WER and Task Completion, and that correlation, unexpectedly, remained more or less linear even for high values of WER. The picture for User Satisfaction metrics is more complex: we found little effect of WER on User Satisfaction for WER less than about 35 to 40% in the 2001 data. The size of the effect of WER on Task Completion was less in 2001 than in 2000, and we believe this difference is due to improved strategies for accomplishing tasks despite speech recognition errors, which is an important accomplishment of the research groups who built the Communicator implementations. We show that additional factors must account for much of the variability in task success, and we present multivariate linear regression models for task success on the 2001 data. We also discuss the apparent gaps in the coverage of our metrics for spoken dialogue systems.
机译:DARPA Communicator计划探索了构建更好的语音对话系统的方法,用户可以通过语音系统单独进行交互,以执行相对复杂的任务,例如旅行计划。在2000年和2001年期间,从会议中收集了两个大型数据集,其中付费用户使用由八个研究小组构建的Communicator系统进行旅行计划。研究小组在两次数据收集之间的10个月中大力改善了他们的系统。在本文中,我们分析了这些数据集,以估计语音识别准确度(通过单词错误率(WER)衡量)对其他指标的影响。我们发现的影响是线性的。我们发现WER与任务完成之间存在相关性,并且即使WER值很高,这种相关性也出乎意料地保持了线性关系。用户满意度指标的情况更为复杂:在2001年的数据中,我们发现WER对WER的用户满意度的影响几乎不到35%至40%。 WER对任务完成的影响的大小在2001年小于2000年,并且我们认为这种差异是由于尽管语音识别错误但改进了的完成任务的策略,这是构建Communicator实现的研究小组的重要成就。我们表明,其他因素必须说明任务成功的大部分可变性,并且我们根据2001年的数据提出了针对任务成功的多元线性回归模型。我们还将讨论口头对话系统指标覆盖面中的明显差距。

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