OLAC Record

Title:OdiEnCorp 1.0
Bibliographic Citation:http://hdl.handle.net/11234/1-2879
Creator:Parida, Shantipriya
Bojar, Ondřej
Date (W3CDTF):2018-11-26T14:54:22Z
Date Available:2018-11-26T14:54:22Z
Description:Data ---- We have collected English-Odia parallel and monolingual data from the available public websites for NLP research in Odia. The parallel corpus consists of English-Odia parallel Bible, Odia digital library, and Odisha Goverment websites. It covers bible, literature, goverment of Odisha and its policies. We have processed the raw data collected from the websites, performed alignments (a mix of manual and automatic alignments) and release the corpus in a form ready for various NLP tasks. The Odia monolingual data consists of Odia-Wikipedia and Odia e-magazine websites. Because the major portion of data is extracted from Odia-Wikipedia, it covers all kinds of domains. The e-magazines data mostly cover the literature domain. We have preprocessed the monolingual data including de-duplication, text normalization, and sentence segmentation to make it ready for various NLP tasks. Corpus Formats -------------- Both corpora are in simple tab-delimited plain text files. The parallel corpus files have three columns: - the original book/source of the sentence pair - the English sentence - the corresponding Odia sentence The monolingual corpus has a varying number of columns: - each line corresponds to one *paragraph* (or related unit) of the original source - each tab-delimited unit corresponds to one *sentence* in the paragraph Data Statistics ---------------- The statistics of the current release is given below. Parallel Corpus Statistics --------------------------- Dataset Sentences #English tokens #Odia tokens ------- --------- ---------------- ------------- Train 27136 706567 604147 Dev 948 21912 19513 Test 1262 28488 24365 ------- --------- ---------------- ------------- Total 29346 756967 648025 Domain Level Statistics ------------------------ Domain Sentences #English tokens #Odia tokens ------------------ --------- ---------------- ------------- Bible 29069 756861 640157 Literature 424 7977 6611 Goverment policies 204 1411 1257 ------------------ --------- ---------------- ------------- Total 29697 766249 648025 Monolingual Corpus Statistics ----------------------------- Paragraphs Sentences #Odia tokens ---------- --------- ------------ 71698 221546 2641308 Domain Level Statistics ----------------------- Domain Paragraphs Sentences #Odia tokens -------------- -------------- --------- ------------- General (wiki) 30468 (42.49%) 102085 1320367 Literature 41230 (57.50%) 119461 1320941 -------------- -------------- --------- ------------- Total 71698 221546 2641308 Citation -------- If you use this corpus, please cite it directly (see above), but please cite also the following paper: Title: OdiEnCorp: Odia-English and Odia-Only Corpus for Machine Translation Author: Shantipriya Parida, Ondrej Bojar, and Satya Ranjan Dash Proceedings of the Third International Conference on Smart Computing & Informatics (SCI) 2018 Series: Smart Innovation, Systems and Technologies (SIST) Publisher: Springer Singapore
Identifier (URI):http://hdl.handle.net/11234/1-2879
Language:Oriya (macrolanguage)
Language (ISO639):ori
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)
Subject:Odia English Parallel Corpus
Odia Monolingual Corpus
English-Odia Machine Translation
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:11234/1-2879
DateStamp:  2021-06-29
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Citation: Parida, Shantipriya; Bojar, Ondřej. 2018. Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL).
Terms: area_Europe country_GB dcmi_Text iso639_eng iso639_ori olac_primary_text

Up-to-date as of: Thu Oct 5 0:40:55 EDT 2023