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Dependencies between Student State and Speech Recognition Problems in Spoken Tutoring Dialogues.

, and . ACL, The Association for Computer Linguistics, (2006)

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Exploring Affect-Context Dependencies for Adaptive System Development., , , and . HLT-NAACL (Short Papers), page 41-44. The Association for Computational Linguistics, (2007)Exploiting Discourse Structure for Spoken Dialogue Performance Analysis., and . EMNLP, page 85-93. ACL, (2006)Classifying turn-level uncertainty using word-level prosody., , and . INTERSPEECH, page 2003-2006. ISCA, (2009)Multi-Gigahertz Testing of Wafer-Level Packaged Devices., , , and . ITC, page 1-10. IEEE Computer Society, (2006)Reliable messaging to millions of users with migratorydata., , , and . Middleware Industry, page 1-7. ACM, (2017)The relative impact of student affect on performance models in a spoken dialogue tutoring system., , and . User Model. User-Adapt. Interact., 18 (1-2): 11-43 (2008)Exploiting Word-level Features for Emotion Prediction., , and . SLT, page 110-113. IEEE, (2006)Dependencies between Student State and Speech Recognition Problems in Spoken Tutoring Dialogues., and . ACL, The Association for Computer Linguistics, (2006)Compact Electromagnetic Bandgap Structures for Notch Band in Ultra-Wideband Applications., and . Sensors, 10 (11): 9620-9629 (2010)Comparing Linguistic Features for Modeling Learning in Computer Tutoring., , , , and . AIED, volume 158 of Frontiers in Artificial Intelligence and Applications, page 270-277. IOS Press, (2007)