Gonzalo Méndez


Adapting Descriptions of People to the Point of View of a Moving Observer
Gonzalo Méndez | Raquel Hervás | Pablo Gervás | Ricardo de la Rosa | Daniel Ruiz
Proceedings of the 11th International Conference on Natural Language Generation

This paper addresses the task of generating descriptions of people for an observer that is moving within a scene. As the observer moves, the descriptions of the people around him also change. A referring expression generation algorithm adapted to this task needs to continuously monitor the changes in the field of view of the observer, his relative position to the people being described, and the relative position of these people to any landmarks around them, and to take these changes into account in the referring expressions generated. This task presents two advantages: many of the mechanisms already available for static contexts may be applied with small adaptations, and it introduces the concept of changing conditions into the task of referring expression generation. In this paper we describe the design of an algorithm that takes these aspects into account in order to create descriptions of people within a 3D virtual environment. The evaluation of this algorithm has shown that, by changing the descriptions in real time according to the observers point of view, they are able to identify the described person quickly and effectively.


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
Proceedings of the 10th International Conference on Natural Language Generation

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.


Riddle Generation using Word Associations
Paloma Galván | Virginia Francisco | Raquel Hervás | Gonzalo Méndez
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In knowledge bases where concepts have associated properties, there is a large amount of comparative information that is implicitly encoded in the values of the properties these concepts share. Although there have been previous approaches to generating riddles, none of them seem to take advantage of structured information stored in knowledge bases such as Thesaurus Rex, which organizes concepts according to the fine grained ad-hoc categories they are placed into by speakers in everyday language, along with associated properties or modifiers. Taking advantage of these shared properties, we have developed a riddle generator that creates riddles about concepts represented as common nouns. The base of these riddles are comparisons between the target concept and other entities that share some of its properties. In this paper, we describe the process we have followed to generate the riddles starting from the target concept and we show the results of the first evaluation we have carried out to test the quality of the resulting riddles.

Mining Knowledge in Storytelling Systems for Narrative Generation
Eugenio Concepción | Pablo Gervás | Gonzalo Méndez
Proceedings of the INLG 2016 Workshop on Computational Creativity in Natural Language Generation

A Challenge Proposal for Narrative Generation Using CNLs
Eugenio Concepción | Gonzalo Méndez | Pablo Gervás | Carlos León
Proceedings of the 9th International Natural Language Generation conference