OLAC Record

Title:Hindi Visual Genome 1.1
Bibliographic Citation:http://hdl.handle.net/11234/1-3267
Creator:Parida, Shantipriya
Bojar, Ondřej
Date (W3CDTF):2020-08-14T20:06:20Z
Date Available:2020-08-14T20:06:20Z
Description:Data ---- Hindi Visual Genome 1.1 is an updated version of Hindi Visual Genome 1.0. The update concerns primarily the text part of Hindi Visual Genome, fixing translation issues reported during WAT 2019 multimodal task. In the image part, only one segment and thus one image were removed from the dataset. Hindi Visual Genome 1.1 serves in "WAT 2020 Multi-Modal Machine Translation Task". Hindi Visual Genome is a multimodal dataset consisting of text and images suitable for English-to-Hindi multimodal machine translation task and multimodal research. We have selected short English segments (captions) from Visual Genome along with associated images and automatically translated them to Hindi with manual post-editing, taking the associated images into account. The training set contains 29K segments. Further 1K and 1.6K segments are provided in a development and test sets, respectively, which follow the same (random) sampling from the original Hindi Visual Genome. A third test set is called ``challenge test set'' consists of 1.4K segments and it was released for WAT2019 multi-modal task. The challenge test set was created 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 - Hindi 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 is given below. Parallel Corpus Statistics --------------------------- Dataset Segments English Words Hindi Words ------- --------- ---------------- ------------- Train 28930 143164 145448 Dev 998 4922 4978 Test 1595 7853 7852 Challenge Test 1400 8186 8639 ------- --------- ---------------- ------------- Total 32923 164125 166917 The word counts are approximate, prior to tokenization. Citation -------- If you use this corpus, please cite the following paper: @article{hindi-visual-genome:2019, title={{Hindi Visual Genome: A Dataset for Multimodal English-to-Hindi Machine Translation}}, author={Parida, Shantipriya and Bojar, Ond{\v{r}}ej and Dash, Satya Ranjan}, journal={Computaci{\'o}n y Sistemas}, volume={23}, number={4}, pages={1499--1505}, year={2019} }
Identifier (URI):http://hdl.handle.net/11234/1-3267
Language (ISO639):eng
Publisher:Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Replaces (URI):http://hdl.handle.net/11234/1-2997
Rights:Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
neural machine translation
English-Hindi parallel corpus
image captioning
image annotation
Type (DCMI):Text
Type (OLAC):primary_text


Archive:  LINDAT/CLARIAH-CZ digital library at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics, Charles University
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OaiIdentifier:  oai:lindat.mff.cuni.cz:11234/1-3267
DateStamp:  2021-06-29
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Citation: Parida, Shantipriya; Bojar, Ondřej. 2020. Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL).
Terms: area_Asia area_Europe country_GB country_IN dcmi_Text iso639_eng iso639_hin olac_primary_text

Up-to-date as of: Thu Oct 5 0:41:07 EDT 2023