David DeVault


2017

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Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue
Kristiina Jokinen | Manfred Stede | David DeVault | Annie Louis
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue

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Using Reinforcement Learning to Model Incrementality in a Fast-Paced Dialogue Game
Ramesh Manuvinakurike | David DeVault | Kallirroi Georgila
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue

We apply Reinforcement Learning (RL) to the problem of incremental dialogue policy learning in the context of a fast-paced dialogue game. We compare the policy learned by RL with a high-performance baseline policy which has been shown to perform very efficiently (nearly as well as humans) in this dialogue game. The RL policy outperforms the baseline policy in offline simulations (based on real user data). We provide a detailed comparison of the RL policy and the baseline policy, including information about how much effort and time it took to develop each one of them. We also highlight the cases where the RL policy performs better, and show that understanding the RL policy can provide valuable insights which can inform the creation of an even better rule-based policy.

2016

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PentoRef: A Corpus of Spoken References in Task-oriented Dialogues
Sina Zarrieß | Julian Hough | Casey Kennington | Ramesh Manuvinakurike | David DeVault | Raquel Fernández | David Schlangen
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

PentoRef is a corpus of task-oriented dialogues collected in systematically manipulated settings. The corpus is multilingual, with English and German sections, and overall comprises more than 20000 utterances. The dialogues are fully transcribed and annotated with referring expressions mapped to objects in corresponding visual scenes, which makes the corpus a rich resource for research on spoken referring expressions in generation and resolution. The corpus includes several sub-corpora that correspond to different dialogue situations where parameters related to interactivity, visual access, and verbal channel have been manipulated in systematic ways. The corpus thus lends itself to very targeted studies of reference in spontaneous dialogue.

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Real-Time Understanding of Complex Discriminative Scene Descriptions
Ramesh Manuvinakurike | Casey Kennington | David DeVault | David Schlangen
Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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Toward incremental dialogue act segmentation in fast-paced interactive dialogue systems
Ramesh Manuvinakurike | Maike Paetzel | Cheng Qu | David Schlangen | David DeVault
Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2015

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“So, which one is it?” The effect of alternative incremental architectures in a high-performance game-playing agent
Maike Paetzel | Ramesh Manuvinakurike | David DeVault
Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2014

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A Demonstration of Dialogue Processing in SimSensei Kiosk
Fabrizio Morbini | David DeVault | Kallirroi Georgila | Ron Artstein | David Traum | Louis-Philippe Morency
Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)

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The Distress Analysis Interview Corpus of human and computer interviews
Jonathan Gratch | Ron Artstein | Gale Lucas | Giota Stratou | Stefan Scherer | Angela Nazarian | Rachel Wood | Jill Boberg | David DeVault | Stacy Marsella | David Traum | Skip Rizzo | Louis-Philippe Morency
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

The Distress Analysis Interview Corpus (DAIC) contains clinical interviews designed to support the diagnosis of psychological distress conditions such as anxiety, depression, and post traumatic stress disorder. The interviews are conducted by humans, human controlled agents and autonomous agents, and the participants include both distressed and non-distressed individuals. Data collected include audio and video recordings and extensive questionnaire responses; parts of the corpus have been transcribed and annotated for a variety of verbal and non-verbal features. The corpus has been used to support the creation of an automated interviewer agent, and for research on the automatic identification of psychological distress.

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A Multimodal Corpus of Rapid Dialogue Games
Maike Paetzel | David Nicolas Racca | David DeVault
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper presents a multimodal corpus of spoken human-human dialogues collected as participants played a series of Rapid Dialogue Games (RDGs). The corpus consists of a collection of about 11 hours of spoken audio, video, and Microsoft Kinect data taken from 384 game interactions (dialogues). The games used for collecting the corpus required participants to give verbal descriptions of linguistic expressions or visual images and were specifically designed to engage players in a fast-paced conversation under time pressure. As a result, the corpus contains many examples of participants attempting to communicate quickly in specific game situations, and it also includes a variety of spontaneous conversational phenomena such as hesitations, filled pauses, overlapping speech, and low-latency responses. The corpus has been created to facilitate research in incremental speech processing for spoken dialogue systems. Potentially, the corpus could be used in several areas of speech and language research, including speech recognition, natural language understanding, natural language generation, and dialogue management.

2013

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Verbal indicators of psychological distress in interactive dialogue with a virtual human
David DeVault | Kallirroi Georgila | Ron Artstein | Fabrizio Morbini | David Traum | Stefan Scherer | Albert Skip Rizzo | Louis-Philippe Morency
Proceedings of the SIGDIAL 2013 Conference

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A method for the approximation of incremental understanding of explicit utterance meaning using predictive models in finite domains
David DeVault | David Traum
Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2012

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Incremental Speech Understanding in a Multi-Party Virtual Human Dialogue System
David DeVault | David Traum
Proceedings of the Demonstration Session at the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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A Demonstration of Incremental Speech Understanding and Confidence Estimation in a Virtual Human Dialogue System
David DeVault | David Traum
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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A Mixed-Initiative Conversational Dialogue System for Healthcare
Fabrizio Morbini | Eric Forbell | David DeVault | Kenji Sagae | David Traum | Albert Rizzo
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

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A Study in How NLU Performance Can Affect the Choice of Dialogue System Architecture
Anton Leuski | David DeVault
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2011

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Toward Learning and Evaluation of Dialogue Policies with Text Examples
David DeVault | Anton Leuski | Kenji Sagae
Proceedings of the SIGDIAL 2011 Conference

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An Approach to the Automated Evaluation of Pipeline Architectures in Natural Language Dialogue Systems
Eliza Margaretha | David DeVault
Proceedings of the SIGDIAL 2011 Conference

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An Evaluation of Alternative Strategies for Implementing Dialogue Policies Using Statistical Classification and Hand-Authored Rules
David DeVault | Anton Leuski | Kenji Sagae
Proceedings of 5th International Joint Conference on Natural Language Processing

2010

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Interpretation of Partial Utterances in Virtual Human Dialogue Systems
Kenji Sagae | David DeVault | David Traum
Proceedings of the NAACL HLT 2010 Demonstration Session

2009

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Can I Finish? Learning When to Respond to Incremental Interpretation Results in Interactive Dialogue
David DeVault | Kenji Sagae | David Traum
Proceedings of the SIGDIAL 2009 Conference

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Learning to Interpret Utterances Using Dialogue History
David DeVault | Matthew Stone
Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009)

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Towards Natural Language Understanding of Partial Speech Recognition Results in Dialogue Systems
Kenji Sagae | Gwen Christian | David DeVault | David Traum
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers

2008

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Making Grammar-Based Generation Easier to Deploy in Dialogue Systems
David DeVault | David Traum | Ron Artstein
Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue

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Practical Grammar-Based NLG from Examples
David DeVault | David Traum | Ron Artstein
Proceedings of the Fifth International Natural Language Generation Conference

2005

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An Information-State Approach to Collaborative Reference
David DeVault | Natalia Kariaeva | Anubha Kothari | Iris Oved | Matthew Stone
Proceedings of the ACL Interactive Poster and Demonstration Sessions

2004

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Interpreting Vague Utterances in Context
David DeVault | Matthew Stone
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics