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        <title>Native Language Identification Using a Mixture of Character and Word N-grams</title>
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            <title>Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications</title>
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        <name type="personal">
            <namePart type="given">Joel</namePart>
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            <namePart type="given">Jill</namePart>
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            <namePart type="given">Claudia</namePart>
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    <abstract>Native language identification (NLI) is the task of determining an author’s native language, based on a piece of his/her writing in a second language. In recent years, NLI has received much attention due to its challenging nature and its applications in language pedagogy and forensic linguistics. We participated in the NLI2017 shared task under the name UT-DSP. In our effort to implement a method for native language identification, we made use of a fusion of character and word N-grams, and achieved an optimal F1-Score of 77.64%, using both essay and speech transcription datasets.</abstract>
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%0 Conference Proceedings
%T Native Language Identification Using a Mixture of Character and Word N-grams
%A Mohammadi, Elham
%A Veisi, Hadi
%A Amini, Hessam
%Y Tetreault, Joel
%Y Burstein, Jill
%Y Leacock, Claudia
%Y Yannakoudakis, Helen
%S Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F mohammadi-etal-2017-native
%X Native language identification (NLI) is the task of determining an author’s native language, based on a piece of his/her writing in a second language. In recent years, NLI has received much attention due to its challenging nature and its applications in language pedagogy and forensic linguistics. We participated in the NLI2017 shared task under the name UT-DSP. In our effort to implement a method for native language identification, we made use of a fusion of character and word N-grams, and achieved an optimal F1-Score of 77.64%, using both essay and speech transcription datasets.
%R 10.18653/v1/W17-5022
%U https://aclanthology.org/W17-5022
%U https://doi.org/10.18653/v1/W17-5022
%P 210-216

Markdown (Informal)

[Native Language Identification Using a Mixture of Character and Word N-grams](https://aclanthology.org/W17-5022) (Mohammadi et al., BEA 2017)

• Native Language Identification Using a Mixture of Character and Word N-grams (Mohammadi et al., BEA 2017)

ACL

• Elham Mohammadi, Hadi Veisi, and Hessam Amini. 2017. Native Language Identification Using a Mixture of Character and Word N-grams. In Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications, pages 210–216, Copenhagen, Denmark. Association for Computational Linguistics.