The following publications are possibly variants of this publication:
- Using Bigrams to Identify Relationships Between Student Certainness States and Tutor Responses in a Spoken Dialogue CorpusKate Forbes-Riley, Diane J. Litman. sigdial 2005: 87-96 [doi]
- Correlating student acoustic-prosodic profiles with student learning in spoken tutoring dialoguesKatherine Forbes-Riley, Diane J. Litman. interspeech 2005: 157-160 [doi]
- Dependencies between Student State and Speech Recognition Problems in Spoken Tutoring DialoguesMihai Rotaru, Diane J. Litman. acl 2006: [doi]
- The relative impact of student affect on performance models in a spoken dialogue tutoring systemKatherine Forbes-Riley, Mihai Rotaru, Diane J. Litman. umuai, 18(1-2):11-43, 2008. [doi]
- Modelling User Satisfaction and Student Learning in a Spoken Dialogue Tutoring System with Generic, Tutoring, and User Affect ParametersKatherine Forbes-Riley, Diane J. Litman. naacl 2006: [doi]
- Recognizing student emotions and attitudes on the basis of utterances in spoken tutoring dialogues with both human and computer tutorsDiane J. Litman, Katherine Forbes-Riley. speech, 48(5):559-590, 2006. [doi]
- Dialogue-Learning Correlations in Spoken Dialogue TutoringKatherine Forbes-Riley, Diane J. Litman, Alison Huettner, Arthur Ward. aied 2005: 225-232
- Using word-level pitch features to better predict student emotions during spoken tutoring dialoguesMihai Rotaru, Diane J. Litman. interspeech 2005: 881-884 [doi]