@inproceedings{bartolini-etal-2014-synsets,
title = "From Synsets to Videos: Enriching {I}tal{W}ord{N}et Multimodally",
author = "Bartolini, Roberto and
Quochi, Valeria and
De Felice, Irene and
Russo, Irene and
Monachini, Monica",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/712_Paper.pdf",
pages = "3110--3117",
abstract = "The paper describes the multimodal enrichment of ItalWordNet action verbs entries by means of an automatic mapping with an ontology of action types instantiated by video scenes (ImagAct). The two resources present important differences as well as interesting complementary features, such that a mapping of these two resources can lead to a an enrichment of IWN, through the connection between synsets and videos apt to illustrate the meaning described by glosses. Here, we describe an approach inspired by ontology matching methods for the automatic mapping of ImagAct video scened onto ItalWordNet sense. The experiments described in the paper are conducted on Italian, but the same methodology can be extended to other languages for which WordNets have been created, since ImagAct is done also for English, Chinese and Spanish. This source of multimodal information can be exploited to design second language learning tools, as well as for language grounding in video action recognition and potentially for robotics.",
}
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<abstract>The paper describes the multimodal enrichment of ItalWordNet action verbs entries by means of an automatic mapping with an ontology of action types instantiated by video scenes (ImagAct). The two resources present important differences as well as interesting complementary features, such that a mapping of these two resources can lead to a an enrichment of IWN, through the connection between synsets and videos apt to illustrate the meaning described by glosses. Here, we describe an approach inspired by ontology matching methods for the automatic mapping of ImagAct video scened onto ItalWordNet sense. The experiments described in the paper are conducted on Italian, but the same methodology can be extended to other languages for which WordNets have been created, since ImagAct is done also for English, Chinese and Spanish. This source of multimodal information can be exploited to design second language learning tools, as well as for language grounding in video action recognition and potentially for robotics.</abstract>
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%0 Conference Proceedings
%T From Synsets to Videos: Enriching ItalWordNet Multimodally
%A Bartolini, Roberto
%A Quochi, Valeria
%A De Felice, Irene
%A Russo, Irene
%A Monachini, Monica
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F bartolini-etal-2014-synsets
%X The paper describes the multimodal enrichment of ItalWordNet action verbs entries by means of an automatic mapping with an ontology of action types instantiated by video scenes (ImagAct). The two resources present important differences as well as interesting complementary features, such that a mapping of these two resources can lead to a an enrichment of IWN, through the connection between synsets and videos apt to illustrate the meaning described by glosses. Here, we describe an approach inspired by ontology matching methods for the automatic mapping of ImagAct video scened onto ItalWordNet sense. The experiments described in the paper are conducted on Italian, but the same methodology can be extended to other languages for which WordNets have been created, since ImagAct is done also for English, Chinese and Spanish. This source of multimodal information can be exploited to design second language learning tools, as well as for language grounding in video action recognition and potentially for robotics.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/712_Paper.pdf
%P 3110-3117
Markdown (Informal)
[From Synsets to Videos: Enriching ItalWordNet Multimodally](http://www.lrec-conf.org/proceedings/lrec2014/pdf/712_Paper.pdf) (Bartolini et al., LREC 2014)
ACL
- Roberto Bartolini, Valeria Quochi, Irene De Felice, Irene Russo, and Monica Monachini. 2014. From Synsets to Videos: Enriching ItalWordNet Multimodally. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 3110–3117, Reykjavik, Iceland. European Language Resources Association (ELRA).