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        <title>Part-of-Speech Annotation of English-Assamese code-mixed texts: Two Approaches</title>
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        <namePart type="given">Ritesh</namePart>
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        <namePart type="given">Manas</namePart>
        <namePart type="given">Jyoti</namePart>
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            <namePart type="family">Sinha</namePart>
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    <abstract>In this paper, we discuss the development of a part-of-speech tagger for English-Assamese code-mixed texts. We provide a comparison of 2 approaches to annotating code-mixed data – a) annotation of the texts from the two languages using monolingual resources from each language and b) annotation of the text through a different resource created specifically for code-mixed data. We present a comparative study of the efforts required in each approach and the final performance of the system. Based on this, we argue that it might be a better approach to develop new technologies using code-mixed data instead of monolingual, ‘clean’ data, especially for those languages where we do not have significant tools and technologies available till now.</abstract>
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%0 Conference Proceedings
%T Part-of-Speech Annotation of English-Assamese code-mixed texts: Two Approaches
%A Kumar, Ritesh
%A Bora, Manas Jyoti
%Y Sinha, Manjira
%Y Dasgupta, Tirthankar
%S Proceedings of the First International Workshop on Language Cognition and Computational Models
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F kumar-bora-2018-part
%X In this paper, we discuss the development of a part-of-speech tagger for English-Assamese code-mixed texts. We provide a comparison of 2 approaches to annotating code-mixed data – a) annotation of the texts from the two languages using monolingual resources from each language and b) annotation of the text through a different resource created specifically for code-mixed data. We present a comparative study of the efforts required in each approach and the final performance of the system. Based on this, we argue that it might be a better approach to develop new technologies using code-mixed data instead of monolingual, ‘clean’ data, especially for those languages where we do not have significant tools and technologies available till now.
%U https://aclanthology.org/W18-4110
%P 94-103

Markdown (Informal)

[Part-of-Speech Annotation of English-Assamese code-mixed texts: Two Approaches](https://aclanthology.org/W18-4110) (Kumar & Bora, LCCM 2018)

• Part-of-Speech Annotation of English-Assamese code-mixed texts: Two Approaches (Kumar & Bora, LCCM 2018)

ACL

• Ritesh Kumar and Manas Jyoti Bora. 2018. Part-of-Speech Annotation of English-Assamese code-mixed texts: Two Approaches. In Proceedings of the First International Workshop on Language Cognition and Computational Models, pages 94–103, Santa Fe, New Mexico, USA. Association for Computational Linguistics.