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ERIC Number: EJ1109955
Record Type: Journal
Publication Date: 2012-Sep
Pages: 71
Abstractor: As Provided
ISSN: EISSN-2330-8516
Identifying Speech Acts in E-Mails: Toward Automated Scoring of the "TOEIC"® E-Mail Task. Research Report. ETS RR-12-16
De Felice, Rachele; Deane, Paul
ETS Research Report Series, Sep 2012
This study proposes an approach to automatically score the "TOEIC"® Writing e-mail task. We focus on one component of the scoring rubric, which notes whether the test-takers have used particular speech acts such as requests, orders, or commitments. We developed a computational model for automated speech act identification and tested it on a corpus of TOEIC responses, achieving up to 79.28% accuracy. This model represents a positive first step toward the development of a more comprehensive scoring model. We also created a corpus of speech actannotated native English workplace e-mails. Comparisons between these and the TOEIC data allow us to assess whether English learners are approximating native models and whether differences between native and non-native data can have negative consequences in the global workplace.
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Publication Type: Journal Articles; Reports - Research; Tests/Questionnaires
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Test of English for International Communication
Grant or Contract Numbers: N/A