Mariët Theune

Also published as: Mariet Theune, M. Theune


2020

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BLISS: An Agent for Collecting Spoken Dialogue Data about Health and Well-being
Jelte van Waterschoot | Iris Hendrickx | Arif Khan | Esther Klabbers | Marcel de Korte | Helmer Strik | Catia Cucchiarini | Mariët Theune
Proceedings of the 12th Language Resources and Evaluation Conference

An important objective in health-technology is the ability to gather information about people’s well-being. Structured interviews can be used to obtain this information, but are time-consuming and not scalable. Questionnaires provide an alternative way to extract such information, though typically lack depth. In this paper, we present our first prototype of the BLISS agent, an artificial intelligent agent which intends to automatically discover what makes people happy and healthy. The goal of Behaviour-based Language-Interactive Speaking Systems (BLISS) is to understand the motivations behind people’s happiness by conducting a personalized spoken dialogue based on a happiness model. We built our first prototype of the model to collect 55 spoken dialogues, in which the BLISS agent asked questions to users about their happiness and well-being. Apart from a description of the BLISS architecture, we also provide details about our dataset, which contains over 120 activities and 100 motivations and is made available for usage.

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Creating a Sentiment Lexicon with Game-Specific Words for Analyzing NPC Dialogue in The Elder Scrolls V: Skyrim
Thérèse Bergsma | Judith van Stegeren | Mariët Theune
Workshop on Games and Natural Language Processing

A weak point of rule-based sentiment analysis systems is that the underlying sentiment lexicons are often not adapted to the domain of the text we want to analyze. We created a game-specific sentiment lexicon for video game Skyrim based on the E-ANEW word list and a dataset of Skyrim’s in-game documents. We calculated sentiment ratings for NPC dialogue using both our lexicon and E-ANEW and compared the resulting sentiment ratings to those of human raters. Both lexicons perform comparably well on our evaluation dialogues, but the game-specific extension performs slightly better on the dominance dimension for dialogue segments and the arousal dimension for full dialogues. To our knowledge, this is the first time that a sentiment analysis lexicon has been adapted to the video game domain.

2019

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Narrative Generation in the Wild: Methods from NaNoGenMo
Judith van Stegeren | Mariët Theune
Proceedings of the Second Workshop on Storytelling

In text generation, generating long stories is still a challenge. Coherence tends to decrease rapidly as the output length increases. Especially for generated stories, coherence of the narrative is an important quality aspect of the output text. In this paper we examine how narrative coherence is attained in the submissions of NaNoGenMo 2018, an online text generation event where participants are challenged to generate a 50,000 word novel. We list the main approaches that were used to generate coherent narratives and link them to scientific literature. Finally, we give recommendations on when to use which approach.

2018

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Downward Compatible Revision of Dialogue Annotation
Harry Bunt | Emer Gilmartin | Simon Keizer | Catherine Pelachaud | Volha Petukhova | Laurent Prévot | Mariët Theune
Proceedings 14th Joint ACL - ISO Workshop on Interoperable Semantic Annotation

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Going Dutch: Creating SimpleNLG-NL
Ruud de Jong | Mariët Theune
Proceedings of the 11th International Conference on Natural Language Generation

This paper presents SimpleNLG-NL, an adaptation of the SimpleNLG surface realisation engine for the Dutch language. It describes a novel method for determining and testing the grammatical constructions to be implemented, using target sentences sampled from a treebank.

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Template-based multilingual football reports generation using Wikidata as a knowledge base
Lorenzo Gatti | Chris van der Lee | Mariët Theune
Proceedings of the 11th International Conference on Natural Language Generation

This paper presents a new version of a football reports generation system called PASS. The original version generated Dutch text and relied on a limited hand-crafted knowledge base. We describe how, in a short amount of time, we extended PASS to produce English texts, exploiting machine translation and Wikidata as a large-scale source of multilingual knowledge.

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Proceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS&NLG)
Jose M. Alonso | Alejandro Catala | Mariët Theune
Proceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS&NLG)

2014

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Why Gender and Age Prediction from Tweets is Hard: Lessons from a Crowdsourcing Experiment
Dong Nguyen | Dolf Trieschnigg | A. Seza Doğruöz | Rilana Gravel | Mariët Theune | Theo Meder | Franciska de Jong
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

2013

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Learning to Extract Folktale Keywords
Dolf Trieschnigg | Dong Nguyen | Mariët Theune
Proceedings of the 7th Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities

2012

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Learning Preferences for Referring Expression Generation: Effects of Domain, Language and Algorithm
Ruud Koolen | Emiel Krahmer | Mariët Theune
INLG 2012 Proceedings of the Seventh International Natural Language Generation Conference

2011

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Generating Varied Narrative Probability Exercises
Mariët Theune | Roan Boer Rookhuiszen | Rieks op den Akker | Hanneke Geerlings
Proceedings of the Sixth Workshop on Innovative Use of NLP for Building Educational Applications

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Report on the Second Second Challenge on Generating Instructions in Virtual Environments (GIVE-2.5)
Kristina Striegnitz | Alexandre Denis | Andrew Gargett | Konstantina Garoufi | Alexander Koller | Mariët Theune
Proceedings of the 13th European Workshop on Natural Language Generation

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The Thumbs Up! Twente system for GIVE 2.5
Saskia Akkersdijk | Marin Langenbach | Frieder Loch | Mariët Theune
Proceedings of the 13th European Workshop on Natural Language Generation

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Does Size Matter – How Much Data is Required to Train a REG Algorithm?
Mariët Theune | Ruud Koolen | Emiel Krahmer | Sander Wubben
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

2010

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Cross-linguistic Attribute Selection for REG: Comparing Dutch and English
Mariët Theune | Ruud Koolen | Emiel Krahmer
Proceedings of the 6th International Natural Language Generation Conference

2009

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Proceedings of the 12th European Workshop on Natural Language Generation (ENLG 2009)
Emiel Krahmer | Mariët Theune
Proceedings of the 12th European Workshop on Natural Language Generation (ENLG 2009)

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Realizing the Costs: Template-Based Surface Realisation in the GRAPH Approach to Referring Expression Generation
Ivo Brugman | Mariët Theune | Emiel Krahmer | Jette Viethen
Proceedings of the 12th European Workshop on Natural Language Generation (ENLG 2009)

2008

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Controlling Redundancy in Referring Expressions
Jette Viethen | Robert Dale | Emiel Krahmer | Mariët Theune | Pascal Touset
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

Krahmer et al.’s (2003) graph-based framework provides an elegant and flexible approach to the generation of referring expressions. In this paper, we present the first reported study that systematically investigates how to tune the parameters of the graph-based framework on the basis of a corpus of human-generated descriptions. We focus in particular on replicating the redundant nature of human referring expressions, whereby properties not strictly necessary for identifying a referent are nonetheless included in descriptions. We show how statistics derived from the corpus data can be integrated to boost the framework’s performance over a non-stochastic baseline.

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GRAPH: The Costs of Redundancy in Referring Expressions
Emiel Krahmer | Mariët Theune | Jette Viethen | Iris Hendrickx
Proceedings of the Fifth International Natural Language Generation Conference

2007

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Which Way to Turn? Guide Orientation in Virtual Way Finding
Mark Evers | Mariët Theune | Joyce Karreman
Proceedings of the Workshop on Embodied Language Processing

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The Narrator: NLG for digital storytelling
Mariët Theune | Nanda Slabbers | Feikje Hielkema
Proceedings of the Eleventh European Workshop on Natural Language Generation (ENLG 07)

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Cueing the Virtual Storyteller: Analysis of cue phrase usage in fairy tales
Manon Penning | Mariët Theune
Proceedings of the Eleventh European Workshop on Natural Language Generation (ENLG 07)

2005

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Squibs and Discussions: Real versus Template-Based Natural Language Generation: A False Opposition?
Kees van Deemter | Emiel Krahmer | Mariët Theune
Computational Linguistics, Volume 31, Number 1, March 2005

1998

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System Demonstration GoalGetter: Generation of Spoken Soccer Reports
Mariet Theune | Esther Klabbers
Natural Language Generation

1997

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Computing prosodic properties in a data-to-speech system
M. Theune | E. Klabbers | J. Odijk | J.R. de Pijper
Concept to Speech Generation Systems

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Contrastive accent in a data-to-speech system
Mariet Theune
35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics