Annotation Data for the paper Automated Generation of Storytelling Vocabulary from Photographs for use in AAC

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Fontana de Vargas, Maurício, 2021, "Annotation Data for the paper Automated Generation of Storytelling Vocabulary from Photographs for use in AAC", https://doi.org/10.5683/SP2/NVI701, Borealis, V1
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Description
Manual annotations of 'Contextual Information Level' and 'Context Description Quality' of VIST-VAL dataset, as described in the paper "Automated Generation of Storytelling Vocabulary from Photographs for Use in AAC" (2021-05-27)
Subject Computer and Information Science
Keyword VIST, AAC
Related Publication M. F. de Vargas, K. Moffatt. 2021. "Automated Generation of Storytelling Vocabulary from Photographs for Use in AAC", in ACL (to appear).
Notes FILES 'all-annotations': include annotations of all 1946 photos from VIST-VAL that have 5 narrative sentences associated. Annotations were made by the first author. 'external-annotations': annotations of 514 photos made by a person unfamiliar with the study, used to calculate the interrater reliability score. DATASET ENTRIES Each key in the json file corresponds to one photo of the VIST-VAL dataset. Each photo entry has the following attributes: photo_id: the original photo id in VIST-VAL azureCaption: the caption generated automatically by the machine learning technique adopted. photo_quality: a score between 0 and 3 based on the number of contextual categories (environment, people/object, activity) it clearly depicts (0 when ambiguous). It is the sum of "photo_quality_location", "photo_quality_subject", and "photo_quality_activity". photo_quality_location: a 0/1 score indicating whether the location of the scene photographed in clearly depicted photo_quality_subject: a 0/1 score indicating whether the subject (person or object) of the scene photographed in clearly depicted photo_quality_activity: a 0/1 score indicating whether the activity present in the scene photographed in clearly depicted azureCaption_quality: a score between 0 and 3 given to the azureCaption generated, according to these rules : 0) not generated or completely unrelated; 1) misses most important elements OR contains most of important elements and a few unrelated elements; 2) contains most of important elements OR all important elements and a few unrelated elements; 3) contains all important elements in the photo and does not contain any unrelated elements. groundTruthSIS: a set of five narrative sentences from VIST-VAL associated with the photo_id
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all-annotations.json
JSON - 1.3 MB
Published May 27, 2021
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MD5: f036d8e2f540158dde97ba9e8955198f
Annotations of all 1946 photos from VIST-VAL that have 5 narrative sentences associated. Annotations were made by the first author.
Data
external-annotations.json
JSON - 376.2 KB
Published May 27, 2021
3 Downloads
MD5: c95bbe7036d31dd20128b615ccb11999
Annotations of 514 photos made by a person unfamiliar with the study, used to calculate the interrater reliability score.
Data
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