OLAC Record oai:lindat.mff.cuni.cz:11234/1-3722

Metadata
Title:		Bengali Visual Genome 1.0
Bibliographic Citation:		http://hdl.handle.net/11234/1-3722
Creator:		Sen, Arghyadeep
		Parida, Shantipriya
		Kotwal, Ketan
		Panda, Subhadarshi
		Bojar, Ondřej
		Dash, Satya Ranjan
Date (W3CDTF):		2022-06-23T09:00:23Z
Date Available:		2022-06-23T09:00:23Z
Description:		Data ------- Bengali Visual Genome (BVG for short) 1.0 has similar goals as Hindi Visual Genome (HVG) 1.1: to support the Bengali language. Bengali Visual Genome 1.0 is the multi-modal dataset in Bengali for machine translation and image captioning. Bengali Visual Genome is a multimodal dataset consisting of text and images suitable for English-to-Bengali multimodal machine translation tasks and multimodal research. We follow the same selection of short English segments (captions) and the associated images from Visual Genome as HGV 1.1 has. For BVG, we manually translated these captions from English to Bengali taking the associated images into account. The manual translation is performed by the native Bengali speakers without referring to any machine translation system. The training set contains 29K segments. Further 1K and 1.6K segments are provided in development and test sets, respectively, which follow the same (random) sampling from the original Hindi Visual Genome. A third test set is called the ``challenge test set'' and consists of 1.4K segments. The challenge test set was created for the WAT2019 multi-modal task by searching for (particularly) ambiguous English words based on the embedding similarity and manually selecting those where the image helps to resolve the ambiguity. The surrounding words in the sentence however also often include sufficient cues to identify the correct meaning of the ambiguous word. Dataset Formats --------------- The multimodal dataset contains both text and images. The text parts of the dataset (train and test sets) are in simple tab-delimited plain text files. All the text files have seven columns as follows: Column1 - image_id Column2 - X Column3 - Y Column4 - Width Column5 - Height Column6 - English Text Column7 - Bengali Text The image part contains the full images with the corresponding image_id as the file name. The X, Y, Width and Height columns indicate the rectangular region in the image described by the caption. Data Statistics --------------- The statistics of the current release are given below. Parallel Corpus Statistics -------------------------- Dataset Segments English Words Bengali Words ---------- -------- ------------- ------------- Train 28930 143115 113978 Dev 998 4922 3936 Test 1595 7853 6408 Challenge Test 1400 8186 6657 ---------- -------- ------------- ------------- Total 32923 164076 130979 The word counts are approximate, prior to tokenization. Citation -------- If you use this corpus, please cite the following paper: @inproceedings{hindi-visual-genome:2022, title= "{Bengali Visual Genome: A Multimodal Dataset for Machine Translation and Image Captioning}", author={Sen, Arghyadeep and Parida, Shantipriya and Kotwal, Ketan and Panda, Subhadarshi and Bojar, Ond{\v{r}}ej and Dash, Satya Ranjan}, editor={Satapathy, Suresh Chandra and Peer, Peter and Tang, Jinshan and Bhateja, Vikrant and Ghosh, Anumoy}, booktitle= {Intelligent Data Engineering and Analytics}, publisher= {Springer Nature Singapore}, address= {Singapore}, pages = {63--70}, isbn = {978-981-16-6624-7}, doi = {10.1007/978-981-16-6624-7_7}, }
Identifier (URI):		http://hdl.handle.net/11234/1-3722
Language:		English
		Bengali
Language (ISO639):		eng
		ben
Publisher:		Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Rights:		Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
		http://creativecommons.org/licenses/by-nc-sa/4.0/
Subject:		multi-modal
		neural machine translation
		image captioning
		Bengali captioning
		English-Bengali Multimodal Corpus
Type:		corpus
Type (DCMI):		Text
Type (OLAC):		primary_text
OLAC Info
Archive:		LINDAT/CLARIAH-CZ digital library at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics, Charles University
Description:		http://www.language-archives.org/archive/lindat.mff.cuni.cz
GetRecord:		OAI-PMH request for OLAC format
GetRecord:		Pre-generated XML file
OAI Info
OaiIdentifier:		oai:lindat.mff.cuni.cz:11234/1-3722
DateStamp:		2022-06-23
GetRecord:		OAI-PMH request for simple DC format
Search Info
Citation:		Sen, Arghyadeep; Parida, Shantipriya; Kotwal, Ketan; Panda, Subhadarshi; Bojar, Ondřej; Dash, Satya Ranjan. 2022. Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL).
Terms:		area_Asia area_Europe country_BD country_GB dcmi_Text iso639_ben iso639_eng olac_primary_text