Large scale datasets for Image and Video Captioning in Italian

The application of Attention-based Deep Neural architectures to the automatic captioning of images and videos is enabling the development of increasingly performing systems. Unfortunately, while image processing is language independent, this does not hold for caption generation. Training such archit...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Scaiella Antonio, Danilo Croce, Roberto Basili
Formato:	article
Lenguaje:	EN
Publicado:	Accademia University Press 2019
Materias:	Social Sciences H Computational linguistics. Natural language processing P98-98.5
Acceso en línea:	https://doaj.org/article/5273e36a79404a07978ed1fcf57fc24a
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:5273e36a79404a07978ed1fcf57fc24a
record_format	dspace
spelling	oai:doaj.org-article:5273e36a79404a07978ed1fcf57fc24a2021-12-02T09:52:19ZLarge scale datasets for Image and Video Captioning in Italian2499-455310.4000/ijcol.478https://doaj.org/article/5273e36a79404a07978ed1fcf57fc24a2019-12-01T00:00:00Zhttp://journals.openedition.org/ijcol/478https://doaj.org/toc/2499-4553The application of Attention-based Deep Neural architectures to the automatic captioning of images and videos is enabling the development of increasingly performing systems. Unfortunately, while image processing is language independent, this does not hold for caption generation. Training such architectures requires the availability of (possibly large-scale) language specific resources, which are not available for many languages, such as Italian.In this paper, we present MSCOCO-it e MSR-VTT-it, two large-scale resources for image and video captioning. They have been derived by applying automatic machine translation to existing resources. Even though this approach is naive and exposed to the gathering of noisy information (depending on the quality of the automatic translator), we experimentally show that robust deep learning is enabled, rather tolerant with respect to such noise. In particular, we improve the state-of-the-art results with respect to image captioning in Italian. Moreover, in the paper we discuss the training of a system that, at the best of our knowledge, is the first video captioning system in Italian.Scaiella AntonioDanilo CroceRoberto BasiliAccademia University PressarticleSocial SciencesHComputational linguistics. Natural language processingP98-98.5ENIJCoL, Vol 5, Iss 2, Pp 49-60 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Social Sciences H Computational linguistics. Natural language processing P98-98.5
spellingShingle	Social Sciences H Computational linguistics. Natural language processing P98-98.5 Scaiella Antonio Danilo Croce Roberto Basili Large scale datasets for Image and Video Captioning in Italian
description	The application of Attention-based Deep Neural architectures to the automatic captioning of images and videos is enabling the development of increasingly performing systems. Unfortunately, while image processing is language independent, this does not hold for caption generation. Training such architectures requires the availability of (possibly large-scale) language specific resources, which are not available for many languages, such as Italian.In this paper, we present MSCOCO-it e MSR-VTT-it, two large-scale resources for image and video captioning. They have been derived by applying automatic machine translation to existing resources. Even though this approach is naive and exposed to the gathering of noisy information (depending on the quality of the automatic translator), we experimentally show that robust deep learning is enabled, rather tolerant with respect to such noise. In particular, we improve the state-of-the-art results with respect to image captioning in Italian. Moreover, in the paper we discuss the training of a system that, at the best of our knowledge, is the first video captioning system in Italian.
format	article
author	Scaiella Antonio Danilo Croce Roberto Basili
author_facet	Scaiella Antonio Danilo Croce Roberto Basili
author_sort	Scaiella Antonio
title	Large scale datasets for Image and Video Captioning in Italian
title_short	Large scale datasets for Image and Video Captioning in Italian
title_full	Large scale datasets for Image and Video Captioning in Italian
title_fullStr	Large scale datasets for Image and Video Captioning in Italian
title_full_unstemmed	Large scale datasets for Image and Video Captioning in Italian
title_sort	large scale datasets for image and video captioning in italian
publisher	Accademia University Press
publishDate	2019
url	https://doaj.org/article/5273e36a79404a07978ed1fcf57fc24a
work_keys_str_mv	AT scaiellaantonio largescaledatasetsforimageandvideocaptioninginitalian AT danilocroce largescaledatasetsforimageandvideocaptioninginitalian AT robertobasili largescaledatasetsforimageandvideocaptioninginitalian
_version_	1718397944592334848

Large scale datasets for Image and Video Captioning in Italian

Ejemplares similares