Exploring the Behavior of Classic REG Algorithms in the Description of Characters in 3D Images

Gonzalo Méndez, Raquel Hervás, Susana Bautista, Adrián Rabadán, Teresa Rodríguez

Abstract
Describing people and characters can be very useful in different contexts, such as computational narrative or image description for the visually impaired. However, a review of the existing literature shows that the automatic generation of people descriptions has not received much attention. Our work focuses on the description of people in snapshots from a 3D environment. First, we have conducted a survey to identify the way in which people describe other people under different conditions. We have used the information extracted from this survey to design several Referring Expression Generation algorithms which produce similar results. We have evaluated these algorithms with users in order to identify which ones generate the best description for specific characters in different situations. The evaluation has shown that, in order to generate good descriptions, a combination of different algorithms has to be used depending on the features and situation of the person to be described.
Anthology ID:
W17-3507
Volume:
Proceedings of the 10th International Conference on Natural Language Generation
Month:
September
Year:
2017
Address:
Santiago de Compostela, Spain
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
61–69
Language:
URL:
https://aclanthology.org/W17-3507
DOI:
10.18653/v1/W17-3507
Bibkey:
Cite (ACL):
Gonzalo Méndez, Raquel Hervás, Susana Bautista, Adrián Rabadán, and Teresa Rodríguez. 2017. Exploring the Behavior of Classic REG Algorithms in the Description of Characters in 3D Images. In Proceedings of the 10th International Conference on Natural Language Generation, pages 61–69, Santiago de Compostela, Spain. Association for Computational Linguistics.
Cite (Informal):
Exploring the Behavior of Classic REG Algorithms in the Description of Characters in 3D Images (Méndez et al., INLG 2017)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/W17-3507.pdf
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