C4.5: programs for machine learning
C4.5: programs for machine learning
Visual explanations: images and quantities, evidence and narrative
Visual explanations: images and quantities, evidence and narrative
Finite state segmentation of discourse into clauses
Extended finite state models of language
Implementing an efficient part-of-speech tagger
Software—Practice & Experience
WordsEye: an automatic text-to-scene conversion system
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Machine Learning
Automatic labeling of semantic roles
Computational Linguistics
A machine learning approach to coreference resolution of noun phrases
Computational Linguistics - Special issue on computational anaphora resolution
Natural language driven image generation
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
TASIP '01 Proceedings of the workshop on Temporal and spatial information processing - Volume 13
Towards automatic animated storyboarding
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Automatic text-to-scene conversion in the traffic accident domain
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part IV
EVA'11 Proceedings of the 2011 international conference on Electronic Visualisation and the Arts
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This paper describes a system to create animated 3D scenes of car accidents from reports written in Swedish. The system has been developed using news reports of varying size and complexity. The text-to-scene conversion process consists of two stages. An information extraction module creates a structured representation of the accident and a visual simulator generates and animates the scene. We first describe the overall structure of the text-to-scene conversion and the structure of the representation. We then explain the information extraction and visualization modules. We show snapshots of the car animation output and we conclude with the results we obtained.