Codeswitched Sentence Creation using Dependency Parsing

Codeswitching has become one of the most common occurrences across multilingual speakers of the world, especially in countries like India which encompasses around 23 official languages with the number of bilingual speakers being around 300 million. The scarcity of Codeswitched data becomes a bottlen...

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Bibliographic Details
Published in2021 IEEE 15th International Conference on Semantic Computing (ICSC) pp. 124 - 129
Main Authors Jain, Dhruval, Prabhu, Arun D, Vatsal, Shubham, Ramena, Gopi, Purre, Naresh
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2021
Subjects
codeswitching
Conferences
data augmentation
dependency parser
Grammar
language modelling
Measurement
Natural language processing
Semantics
sentiment analysis
Syntactics
Task analysis
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Summary:Codeswitching has become one of the most common occurrences across multilingual speakers of the world, especially in countries like India which encompasses around 23 official languages with the number of bilingual speakers being around 300 million. The scarcity of Codeswitched data becomes a bottleneck in the exploration of this domain with respect to various Natural Language Processing (NLP) tasks. We thus present a novel algorithm which harnesses the syntactic structure of English grammar to develop grammatically sensible Codeswitched versions of English-Hindi, English-Marathi and English-Kannada data. Apart from maintaining the grammatical sanity to a great extent, our methodology also guarantees abundant generation of data from a minuscule snapshot of given data. We use multiple datasets to showcase the capabilities of our algorithm while at the same time we assess the quality of generated Codeswitched data using some qualitative metrics along with providing baseline results for couple of NLP tasks.
DOI:10.1109/ICSC50631.2021.00030