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Bits_Pilani@INLI-FIRE-2017:Indian Native Language Identification using Deep Learning

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dc.contributor.author Sharma, Yashvardhan
dc.date.accessioned 2023-01-02T10:48:12Z
dc.date.available 2023-01-02T10:48:12Z
dc.date.issued 2017
dc.identifier.uri https://ceur-ws.org/Vol-2036/T4-7.pdf
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8224
dc.description.abstract The task of Native Language Identification involves identifying the prior or first learnt language of a user based on his writing technique and/or analysis of speech and phonetics in second language. There is a surplus of such data present on social media sites and organised dataset from bodies like Educational Testing Service(ETS), which can be exploited to develop language learning systems and forensic linguistics. In this paper we propose a deep neural network for this task using hierarchical paragraph encoder with attention mechanism to identify relevant features over tendencies and errors a user makes with second language for the INLI task in FIRE 2017. The task involves six Indian languages as prior/native set and english as the second language which has been collected from user's social media account. en_US
dc.language.iso en en_US
dc.publisher CEUR en_US
dc.subject Computer Science en_US
dc.subject Native Language Identification en_US
dc.subject Natural Language Processing en_US
dc.subject Deep Learning en_US
dc.subject Neural networks en_US
dc.title Bits_Pilani@INLI-FIRE-2017:Indian Native Language Identification using Deep Learning en_US
dc.type Article en_US


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