BertOdia: BERT Pre-training for Low Resource Odia Language
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A4PDW2E5E" target="_blank" >RIV/00216208:11320/22:4PDW2E5E - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-981-16-8739-6_32" target="_blank" >https://doi.org/10.1007/978-981-16-8739-6_32</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-981-16-8739-6_32" target="_blank" >10.1007/978-981-16-8739-6_32</a>
Alternative languages
Result language
angličtina
Original language name
BertOdia: BERT Pre-training for Low Resource Odia Language
Original language description
Odia language is one of the 30 most spoken languages in the world. It is spoken in the Indian state called Odisha. Odia language lacks online content and resources for natural language processing (NLP) research. There is a great need for a better language model for the low resource Odia language, which can be used for many downstream NLP tasks. In this paper, we introduce a Bert-based language model, pre-trained on 430,000 Odia sentences. We also evaluate the model on the well-known Kaggle Odia news classification dataset (BertOdia: 96%, RoBERTaOdia: 92%, and ULMFit: 91.9% classification accuracy), and perform a comparison study with multilingual Bidirectional Encoder Representations from Transformers (BERT) supporting Odia. The model will be released publicly for the researchers to explore other NLP tasks.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Biologically Inspired Techniques in Many Criteria Decision Making
ISBN
978-981-16-8739-6
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
345-355
Publisher name
Springer Nature
Place of publication
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Event location
Singapore
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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