A Multimodal Dialog System for Language Assessment: Current State and Future Directions. Issue 1 (2nd May 2017)

• Record Type: Journal Article
• Authors: Suendermann‐Oeft, David; Ramanarayanan, Vikram; Yu, Zhou; Qian, Yao; Evanini, Keelan; Lange, Patrick; Wang, Xinhao; Zechner, Klaus
• Is Part Of: ETS research report series. Issue 1(2017)
• Page Start: 1
• Page End: 7
• Publication Date: 2017-05-02
• Subjects: Multimodal analysis -- dialog system -- language assessment -- language learning -- speech recognition -- speaker recognition; Universities and colleges -- Entrance examinations; Universities and colleges -- Graduate work -- Examinations; Universities and colleges -- United States -- Entrance examinations; Universities and colleges -- United States -- Graduate work -- Examinations; Graduate Record Examination; Educational tests and measurements; Social sciences; Education -- Research; Education -- Research; Educational tests and measurements; Graduate Record Examination; Social sciences; Universities and colleges -- Entrance examinations; Universities and colleges -- Graduate work -- Examinations; United States; 378
• DOI: 10.1002/ets2.12149
• Languages: English
• ISSNs: 2330-8516

Abstract

Abstract: We present work in progress on a multimodal dialog system for English language assessment using a modular cloud‐based architecture adhering to open industry standards. Among the modules being developed for the system, multiple modules heavily exploit machine learning techniques, including speech recognition, spoken language proficiency rating, speaker recognition, and the scoring of behaviors in multimodal data streams. Abstract : Report Number: ETS RR‐17–21