<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="banerjee-bhattacharyya-2018-meaningless">
    <titleInfo>
        <title>Meaningless yet meaningful: Morphology grounded subword-level NMT</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Tamali</namePart>
        <namePart type="family">Banerjee</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Pushpak</namePart>
        <namePart type="family">Bhattacharyya</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2018-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Second Workshop on Subword/Character LEvel Models</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Manaal</namePart>
            <namePart type="family">Faruqui</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Hinrich</namePart>
            <namePart type="family">Schütze</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Isabel</namePart>
            <namePart type="family">Trancoso</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Yulia</namePart>
            <namePart type="family">Tsvetkov</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Yadollah</namePart>
            <namePart type="family">Yaghoobzadeh</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">New Orleans</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We explore the use of two independent subsystems Byte Pair Encoding (BPE) and Morfessor as basic units for subword-level neural machine translation (NMT). We show that, for linguistically distant language-pairs Morfessor-based segmentation algorithm produces significantly better quality translation than BPE. However, for close language-pairs BPE-based subword-NMT may translate better than Morfessor-based subword-NMT. We propose a combined approach of these two segmentation algorithms Morfessor-BPE (M-BPE) which outperforms these two baseline systems in terms of BLEU score. Our results are supported by experiments on three language-pairs: English-Hindi, Bengali-Hindi and English-Bengali.</abstract>
    <identifier type="citekey">banerjee-bhattacharyya-2018-meaningless</identifier>
    <identifier type="doi">10.18653/v1/W18-1207</identifier>
    <location>
        <url>https://aclanthology.org/W18-1207</url>
    </location>
    <part>
        <date>2018-06</date>
        <extent unit="page">
            <start>55</start>
            <end>60</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Meaningless yet meaningful: Morphology grounded subword-level NMT
%A Banerjee, Tamali
%A Bhattacharyya, Pushpak
%Y Faruqui, Manaal
%Y Schütze, Hinrich
%Y Trancoso, Isabel
%Y Tsvetkov, Yulia
%Y Yaghoobzadeh, Yadollah
%S Proceedings of the Second Workshop on Subword/Character LEvel Models
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans
%F banerjee-bhattacharyya-2018-meaningless
%X We explore the use of two independent subsystems Byte Pair Encoding (BPE) and Morfessor as basic units for subword-level neural machine translation (NMT). We show that, for linguistically distant language-pairs Morfessor-based segmentation algorithm produces significantly better quality translation than BPE. However, for close language-pairs BPE-based subword-NMT may translate better than Morfessor-based subword-NMT. We propose a combined approach of these two segmentation algorithms Morfessor-BPE (M-BPE) which outperforms these two baseline systems in terms of BLEU score. Our results are supported by experiments on three language-pairs: English-Hindi, Bengali-Hindi and English-Bengali.
%R 10.18653/v1/W18-1207
%U https://aclanthology.org/W18-1207
%U https://doi.org/10.18653/v1/W18-1207
%P 55-60

Markdown (Informal)

[Meaningless yet meaningful: Morphology grounded subword-level NMT](https://aclanthology.org/W18-1207) (Banerjee & Bhattacharyya, SCLeM 2018)

• Meaningless yet meaningful: Morphology grounded subword-level NMT (Banerjee & Bhattacharyya, SCLeM 2018)

ACL

• Tamali Banerjee and Pushpak Bhattacharyya. 2018. Meaningless yet meaningful: Morphology grounded subword-level NMT. In Proceedings of the Second Workshop on Subword/Character LEvel Models, pages 55–60, New Orleans. Association for Computational Linguistics.