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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：结合引发的仿制和流利特征进行口语熟练程度

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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：口语检测的自动分级近年来一直是众多研究的主题。几个障碍在实现这一目标的过程中。最近的工作表明，一种称为引出的模仿（EI）的测试技术，可以准确地接近全球口语熟练程度。然而，这种测试方法不包含语言的一些基本方面，例如流利程度。其他工作提出了另一种测试技术，模拟语音（SS），作为可以提供自动流畅度量的ei的补充或替代品。在这项工作中，我们研究了从SS测试和EI测试分数提取的流利功能的组合，因为更准确地预测口语熟练程度的手段。使用机器学习和统计建模，我们确定从SS测试中自动提取的功能最佳预测的手续的SS测试结果，并证明为这些模型添加EI分数的益处。结果表明，EI和流利功能的组合确实更有效地预测了手续的SS测试分数。我们终于讨论了这项工作对未来的自动化口头测试方案的影响。

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