<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="al-badrashiny-diab-2016-lili">
    <titleInfo>
        <title>LILI: A Simple Language Independent Approach for Language Identification</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Mohamed</namePart>
        <namePart type="family">Al-Badrashiny</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Mona</namePart>
        <namePart type="family">Diab</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2016-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Rashmi</namePart>
            <namePart type="family">Prasad</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>The COLING 2016 Organizing Committee</publisher>
            <place>
                <placeTerm type="text">Osaka, Japan</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We introduce a generic Language Independent Framework for Linguistic Code Switch Point Detection. The system uses characters level 5-grams and word level unigram language models to train a conditional random fields (CRF) model for classifying input words into various languages. We test our proposed framework and compare it to the state-of-the-art published systems on standard data sets from several language pairs: English-Spanish, Nepali-English, English-Hindi, Arabizi (Refers to Arabic written using the Latin/Roman script)-English, Arabic-Engari (Refers to English written using Arabic script), Modern Standard Arabic(MSA)-Egyptian, Levantine-MSA, Gulf-MSA, one more English-Spanish, and one more MSA-EGY. The overall weighted average F-score of each language pair are 96.4%, 97.3%, 98.0%, 97.0%, 98.9%, 86.3%, 88.2%, 90.6%, 95.2%, and 85.0% respectively. The results show that our approach despite its simplicity, either outperforms or performs at comparable levels to state-of-the-art published systems.</abstract>
    <identifier type="citekey">al-badrashiny-diab-2016-lili</identifier>
    <location>
        <url>https://aclanthology.org/C16-1115</url>
    </location>
    <part>
        <date>2016-12</date>
        <extent unit="page">
            <start>1211</start>
            <end>1219</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T LILI: A Simple Language Independent Approach for Language Identification
%A Al-Badrashiny, Mohamed
%A Diab, Mona
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F al-badrashiny-diab-2016-lili
%X We introduce a generic Language Independent Framework for Linguistic Code Switch Point Detection. The system uses characters level 5-grams and word level unigram language models to train a conditional random fields (CRF) model for classifying input words into various languages. We test our proposed framework and compare it to the state-of-the-art published systems on standard data sets from several language pairs: English-Spanish, Nepali-English, English-Hindi, Arabizi (Refers to Arabic written using the Latin/Roman script)-English, Arabic-Engari (Refers to English written using Arabic script), Modern Standard Arabic(MSA)-Egyptian, Levantine-MSA, Gulf-MSA, one more English-Spanish, and one more MSA-EGY. The overall weighted average F-score of each language pair are 96.4%, 97.3%, 98.0%, 97.0%, 98.9%, 86.3%, 88.2%, 90.6%, 95.2%, and 85.0% respectively. The results show that our approach despite its simplicity, either outperforms or performs at comparable levels to state-of-the-art published systems.
%U https://aclanthology.org/C16-1115
%P 1211-1219

Markdown (Informal)

[LILI: A Simple Language Independent Approach for Language Identification](https://aclanthology.org/C16-1115) (Al-Badrashiny & Diab, COLING 2016)

• LILI: A Simple Language Independent Approach for Language Identification (Al-Badrashiny & Diab, COLING 2016)

ACL

• Mohamed Al-Badrashiny and Mona Diab. 2016. LILI: A Simple Language Independent Approach for Language Identification. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1211–1219, Osaka, Japan. The COLING 2016 Organizing Committee.