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Bamdev, Pakhi; Grover, Manraj Singh; Singla, Yaman Kumar; Vafaee, Payman; Hama, Mika; Shah, Rajiv Ratn – International Journal of Artificial Intelligence in Education, 2023
English proficiency assessments have become a necessary metric for filtering and selecting prospective candidates for both academia and industry. With the rise in demand for such assessments, it has become increasingly necessary to have the automated human-interpretable results to prevent inconsistencies and ensure meaningful feedback to the…
Descriptors: Language Proficiency, Automation, Scoring, Speech Tests
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
Gayraud, Frederique; Lee, Hye-Ran; Barkat-Defradas, Melissa – Clinical Linguistics & Phonetics, 2011
Psycholinguistic studies dealing with Alzheimer's disease (AD) commonly consider verbal aspects of language. In this article, we investigated both verbal and non-verbal aspects of speech production in AD. We used pauses and hesitations as markers of planning difficulties and hypothesized that AD patients show different patterns in the process of…
Descriptors: Psycholinguistics, Older Adults, Alzheimers Disease, Patients

Naro, Anthony Julius; Scherre, Maria Marta Pereira – Language Variation and Change, 1996
Discusses a study of concord phenomena in spoken Brazilian Portuguese. Findings indicate the presence of disfluencies, including apparent corrections, in about 15% of the relevant tokens in the corpus of recorded speech data. It is concluded that speech is not overly laden with errors, and there is nothing in the data to mislead the language…
Descriptors: Classification, Discourse Analysis, Error Analysis (Language), Error Correction