Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/26431
Appears in Collections:Biological and Environmental Sciences Journal Articles
Title: The REAL corpus: A crowd-sourced Corpus of human generated and evaluated spatial references to real-world urban scenes
Author(s): Bartie, Phil
Mackaness, William
Gkatzia, Dimitra
Rieser, Verena
Keywords: Image Descriptions
Spatial Referring Expressions
Urban Scenes
Vision and Language
Issue Date: 2016
Citation: Bartie P, Mackaness W, Gkatzia D & Rieser V (2016) The REAL corpus: A crowd-sourced Corpus of human generated and evaluated spatial references to real-world urban scenes In: Calzolari N, Choukri K, Mazo H, Moreno A, Declerck T, Goggi S, Grobelnik M, Odijk J, Piperidis S, Maegaard B, Mariani J (ed.) Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016, Paris: European Language Resources Association (ELRA). 10th International Conference on Language Resources and Evaluation, LREC 2016, 23.5.2016 - 28.5.2016, Portoroz, Slovenia, pp. 2153-2155.
Abstract: We present a newly crowd-sourced data set of natural language references to objects anchored in complex urban scenes (In short: The REAL Corpus – Referring Expressions Anchored Language). The REAL corpus contains a collection of images of real-world urban scenes together with verbal descriptions of target objects generated by humans, paired with data on how successful other people were able to identify the same object based on these descriptions. In total, the corpus contains 32 images with on average 27 descriptions per image and 3 verifications for each description. In addition, the corpus is annotated with a variety of linguistically motivated features. The paper highlights issues posed by collecting data using crowd-sourcing with an unrestricted input format, as well as using real-world urban scenes. The corpus will be released via the ELRA repository as part of this submission.
URL: http://www.lrec-conf.org/proceedings/lrec2016/pdf/1035_Paper.pdf
Rights: The LREC 2016 Proceedings are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/)

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