<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="bentz-etal-2016-comparison">
    <titleInfo>
        <title>A Comparison Between Morphological Complexity Measures: Typological Data vs. Language Corpora</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Christian</namePart>
        <namePart type="family">Bentz</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Tatyana</namePart>
        <namePart type="family">Ruzsics</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Alexander</namePart>
        <namePart type="family">Koplenig</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Tanja</namePart>
        <namePart type="family">Samardžić</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2016-dec</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)</title>
        </titleInfo>
        <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>Language complexity is an intriguing phenomenon argued to play an important role in both language learning and processing. The need to compare languages with regard to their complexity resulted in a multitude of approaches and methods, ranging from accounts targeting specific structural features to global quantification of variation more generally. In this paper, we investigate the degree to which morphological complexity measures are mutually correlated in a sample of more than 500 languages of 101 language families. We use human expert judgements from the World Atlas of Language Structures (WALS), and compare them to four quantitative measures automatically calculated from language corpora. These consist of three previously defined corpus-derived measures, which are all monolingual, and one new measure based on automatic word-alignment across pairs of languages. We find strong correlations between all the measures, illustrating that both expert judgements and automated approaches converge to similar complexity ratings, and can be used interchangeably.</abstract>
    <identifier type="citekey">bentz-etal-2016-comparison</identifier>
    <location>
        <url>https://aclanthology.org/W16-4117</url>
    </location>
    <part>
        <date>2016-dec</date>
        <extent unit="page">
            <start>142</start>
            <end>153</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T A Comparison Between Morphological Complexity Measures: Typological Data vs. Language Corpora
%A Bentz, Christian
%A Ruzsics, Tatyana
%A Koplenig, Alexander
%A Samardžić, Tanja
%S Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)
%D 2016
%8 dec
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F bentz-etal-2016-comparison
%X Language complexity is an intriguing phenomenon argued to play an important role in both language learning and processing. The need to compare languages with regard to their complexity resulted in a multitude of approaches and methods, ranging from accounts targeting specific structural features to global quantification of variation more generally. In this paper, we investigate the degree to which morphological complexity measures are mutually correlated in a sample of more than 500 languages of 101 language families. We use human expert judgements from the World Atlas of Language Structures (WALS), and compare them to four quantitative measures automatically calculated from language corpora. These consist of three previously defined corpus-derived measures, which are all monolingual, and one new measure based on automatic word-alignment across pairs of languages. We find strong correlations between all the measures, illustrating that both expert judgements and automated approaches converge to similar complexity ratings, and can be used interchangeably.
%U https://aclanthology.org/W16-4117
%P 142-153

Markdown (Informal)

[A Comparison Between Morphological Complexity Measures: Typological Data vs. Language Corpora](https://aclanthology.org/W16-4117) (Bentz et al., 2016)

• A Comparison Between Morphological Complexity Measures: Typological Data vs. Language Corpora (Bentz et al., 2016)

ACL

• Christian Bentz, Tatyana Ruzsics, Alexander Koplenig, and Tanja Samardžić. 2016. A Comparison Between Morphological Complexity Measures: Typological Data vs. Language Corpora. In Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC), pages 142–153, Osaka, Japan. The COLING 2016 Organizing Committee.