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首页> 外文会议>9th International conference on language resources and evaluation >Combining elicited imitation and fluency features for oral proficiency measurement
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Combining elicited imitation and fluency features for oral proficiency measurement

机译：结合诱发模仿和流利性特征进行口语能力测量

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摘要

The automatic grading of oral language tests has been the subject of much research in recent years. Several obstacles lie in the way of achieving this goal. Recent work suggests a testing technique called elicited imitation (EI) that can serve to accurately approximate global oral proficiency. This testing methodology, however, does not incorporate some fundamental aspects of language, such as fluency. Other work has suggested another testing technique, simulated speech (SS), as a supplement or an alternative to EI that can provide automated fluency metrics. In this work, we investigate a combination of fluency features extracted from SS tests and EI test scores as a means to more accurately predict oral language proficiency. Using machine learning and statistical modeling, we identify which features automatically extracted from SS tests best predicted hand-scored SS test results, and demonstrate the benefit of adding EI scores to these models. Results indicate that the combination of EI and fluency features do indeed more effectively predict hand-scored SS test scores. We finally discuss implications of this work for future automated oral testing scenarios.
机译：近年来，口语测试的自动评分一直是许多研究的主题。实现这一目标的方式有几个障碍。最近的工作提出了一种称为诱导模仿（EI）的测试技术，可以准确地估算出全球的口语水平。但是，这种测试方法没有包含语言的某些基本方面，例如流利程度。其他工作提出了另一种测试技术，即模拟语音（SS），作为EI的补充或替代，可以提供自动流利度指标。在这项工作中，我们调查了从SS测试和EI测试成绩中提取的流利度特征的组合，以更准确地预测口语水平。使用机器学习和统计建模，我们确定从SS测试中自动提取出哪些功能可以最好地预测手动计分的SS测试结果，并证明将EI分数添加到这些模型中的好处。结果表明，EI和流利性功能的组合确实确实可以更有效地预测手动得分的SS测试成绩。最后，我们讨论了这项工作对将来的自动口试场景的影响。

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