Kate Forbes-Riley

Also published as: Katherine Forbes Riley, Katherine Forbes, Katherine Forbes-Riley, Kate Forbes


2017

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Towards Full Text Shallow Discourse Relation Annotation: Experiments with Cross-Paragraph Implicit Relations in the PDTB
Rashmi Prasad | Katherine Forbes Riley | Alan Lee
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue

Full text discourse parsing relies on texts comprehensively annotated with discourse relations. To this end, we address a significant gap in the inter-sentential discourse relations annotated in the Penn Discourse Treebank (PDTB), namely the class of cross-paragraph implicit relations, which account for 30% of inter-sentential relations in the corpus. We present our annotation study to explore the incidence rate of adjacent vs. non-adjacent implicit relations in cross-paragraph contexts, and the relative degree of difficulty in annotating them. Our experiments show a high incidence of non-adjacent relations that are difficult to annotate reliably, suggesting the practicality of backing off from their annotation to reduce noise for corpus-based studies. Our resulting guidelines follow the PDTB adjacency constraint for implicits while employing an underspecified representation of non-adjacent implicits, and yield 62% inter-annotator agreement on this task.

2016

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Inferring Discourse Relations from PDTB-style Discourse Labels for Argumentative Revision Classification
Fan Zhang | Diane Litman | Katherine Forbes Riley
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers

Penn Discourse Treebank (PDTB)-style annotation focuses on labeling local discourse relations between text spans and typically ignores larger discourse contexts. In this paper we propose two approaches to infer discourse relations in a paragraph-level context from annotated PDTB labels. We investigate the utility of inferring such discourse information using the task of revision classification. Experimental results demonstrate that the inferred information can significantly improve classification performance compared to baselines, not only when PDTB annotation comes from humans but also from automatic parsers.

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Extracting PDTB Discourse Relations from Student Essays
Kate Forbes-Riley | Fan Zhang | Diane Litman
Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2014

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Evaluating a Spoken Dialogue System that Detects and Adapts to User Affective States
Diane Litman | Katherine Forbes-Riley
Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)

2012

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Intrinsic and Extrinsic Evaluation of an Automatic User Disengagement Detector for an Uncertainty-Adaptive Spoken Dialogue System
Kate Forbes-Riley | Diane Litman | Heather Friedberg | Joanna Drummond
Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Adapting to Multiple Affective States in Spoken Dialogue
Kate Forbes-Riley | Diane Litman
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2011

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Using Performance Trajectories to Analyze the Immediate Impact of User State Misclassification in an Adaptive Spoken Dialogue System
Kate Forbes-Riley | Diane Litman
Proceedings of the SIGDIAL 2011 Conference

2009

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Spoken Tutorial Dialogue and the Feeling of Another’s Knowing
Diane Litman | Kate Forbes-Riley
Proceedings of the SIGDIAL 2009 Conference

2008

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Uncertainty Corpus: Resource to Study User Affect in Complex Spoken Dialogue Systems
Kate Forbes-Riley | Diane Litman | Scott Silliman | Amruta Purandare
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

We present a corpus of spoken dialogues between students and an adaptive Wizard-of-Oz tutoring system, in which student uncertainty was manually annotated in real-time. We detail the corpus contents, including speech files, transcripts, annotations, and log files, and we discuss possible future uses by the computational linguistics community as a novel resource for studying naturally occurring user affect and adaptation in complex spoken dialogue systems.

2007

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Exploring Affect-Context Dependencies for Adaptive System Development
Kate Forbes-Riley | Mihai Rotaru | Diane Litman | Joel Tetreault
Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers

2006

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Modelling User Satisfaction and Student Learning in a Spoken Dialogue Tutoring System with Generic, Tutoring, and User Affect Parameters
Kate Forbes-Riley | Diane Litman
Proceedings of the Human Language Technology Conference of the NAACL, Main Conference

2005

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Using Bigrams to Identify Relationships Between Student Certainness States and Tutor Responses in a Spoken Dialogue Corpus
Kate Forbes-Riley | Diane J. Litman
Proceedings of the 6th SIGdial Workshop on Discourse and Dialogue

2004

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Predicting Student Emotions in Computer-Human Tutoring Dialogues
Diane J. Litman | Kate Forbes-Riley
Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04)

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Predicting Emotion in Spoken Dialogue from Multiple Knowledge Sources
Kate Forbes-Riley | Diane Litman
Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics: HLT-NAACL 2004

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Annotating Student Emotional States in Spoken Tutoring Dialogues
Diane J. Litman | Kate Forbes-Riley
Proceedings of the 5th SIGdial Workshop on Discourse and Dialogue at HLT-NAACL 2004

2003

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A Comparison of Tutor and Student Behavior in Speech Versus Text Based Tutoring
Carolyn P. Rosé | Diane Litman | Dumisizwe Bhembe | Kate Forbes | Scott Silliman | Ramesh Srivastava | Kurt VanLehn
Proceedings of the HLT-NAACL 03 Workshop on Building Educational Applications Using Natural Language Processing

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Anaphoric arguments of discourse connectives: Semantic properties of antecedents versus non-antecedents
Eleni Miltsakaki | Cassandre Creswell | Katherine Forbes | Aravind Joshi | Bonnie Webber
Proceedings of the 2003 EACL Workshop on The Computational Treatment of Anaphora

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Towards Emotion Prediction in Spoken Tutoring Dialogues
Diane Litman | Kate Forbes | Scott Silliman
Companion Volume of the Proceedings of HLT-NAACL 2003 - Short Papers

2002

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A Semantic Account of Adverbials as Discourse Connectives
Kate Forbes | Bonnie Webber
Proceedings of the Third SIGdial Workshop on Discourse and Dialogue