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Xi, Xiaoming; Higgins, Derrick; Zechner, Klaus; Williamson, David – Language Testing, 2012
This paper compares two alternative scoring methods--multiple regression and classification trees--for an automated speech scoring system used in a practice environment. The two methods were evaluated on two criteria: construct representation and empirical performance in predicting human scores. The empirical performance of the two scoring models…
Descriptors: Scoring, Classification, Weighted Scores, Comparative Analysis
Zhang, Bo – Language Testing, 2010
This article investigates how measurement models and statistical procedures can be applied to estimate the accuracy of proficiency classification in language testing. The paper starts with a concise introduction of four measurement models: the classical test theory (CTT) model, the dichotomous item response theory (IRT) model, the testlet response…
Descriptors: Language Tests, Classification, Item Response Theory, Statistical Analysis
Franco, Horacio; Bratt, Harry; Rossier, Romain; Rao Gadde, Venkata; Shriberg, Elizabeth; Abrash, Victor; Precoda, Kristin – Language Testing, 2010
SRI International's EduSpeak[R] system is a software development toolkit that enables developers of interactive language education software to use state-of-the-art speech recognition and pronunciation scoring technology. Automatic pronunciation scoring allows the computer to provide feedback on the overall quality of pronunciation and to point to…
Descriptors: Feedback (Response), Sentences, Oral Language, Predictor Variables

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