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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/8224
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dc.contributor.authorSharma, Yashvardhan-
dc.date.accessioned2023-01-02T10:48:12Z-
dc.date.available2023-01-02T10:48:12Z-
dc.date.issued2017-
dc.identifier.urihttps://ceur-ws.org/Vol-2036/T4-7.pdf-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8224-
dc.description.abstractThe 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.isoenen_US
dc.publisherCEURen_US
dc.subjectComputer Scienceen_US
dc.subjectNative Language Identificationen_US
dc.subjectNatural Language Processingen_US
dc.subjectDeep Learningen_US
dc.subjectNeural networksen_US
dc.titleBits_Pilani@INLI-FIRE-2017:Indian Native Language Identification using Deep Learningen_US
dc.typeArticleen_US
Appears in Collections:Department of Computer Science and Information Systems

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