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        <title>Fine-grained evaluation of German-English Machine Translation based on a Test Suite</title>
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    <name type="personal">
        <namePart type="given">Vivien</namePart>
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            <title>Proceedings of the Third Conference on Machine Translation: Shared Task Papers</title>
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    <abstract>We present an analysis of 16 state-of-the-art MT systems on German-English based on a linguistically-motivated test suite. The test suite has been devised manually by a team of language professionals in order to cover a broad variety of linguistic phenomena that MT often fails to translate properly. It contains 5,000 test sentences covering 106 linguistic phenomena in 14 categories, with an increased focus on verb tenses, aspects and moods. The MT outputs are evaluated in a semi-automatic way through regular expressions that focus only on the part of the sentence that is relevant to each phenomenon. Through our analysis, we are able to compare systems based on their performance on these categories. Additionally, we reveal strengths and weaknesses of particular systems and we identify grammatical phenomena where the overall performance of MT is relatively low.</abstract>
    <identifier type="citekey">macketanz-etal-2018-fine</identifier>
    <identifier type="doi">10.18653/v1/W18-6436</identifier>
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%0 Conference Proceedings
%T Fine-grained evaluation of German-English Machine Translation based on a Test Suite
%A Macketanz, Vivien
%A Avramidis, Eleftherios
%A Burchardt, Aljoscha
%A Uszkoreit, Hans
%S Proceedings of the Third Conference on Machine Translation: Shared Task Papers
%D 2018
%8 oct
%I Association for Computational Linguistics
%C Belgium, Brussels
%F macketanz-etal-2018-fine
%X We present an analysis of 16 state-of-the-art MT systems on German-English based on a linguistically-motivated test suite. The test suite has been devised manually by a team of language professionals in order to cover a broad variety of linguistic phenomena that MT often fails to translate properly. It contains 5,000 test sentences covering 106 linguistic phenomena in 14 categories, with an increased focus on verb tenses, aspects and moods. The MT outputs are evaluated in a semi-automatic way through regular expressions that focus only on the part of the sentence that is relevant to each phenomenon. Through our analysis, we are able to compare systems based on their performance on these categories. Additionally, we reveal strengths and weaknesses of particular systems and we identify grammatical phenomena where the overall performance of MT is relatively low.
%R 10.18653/v1/W18-6436
%U https://aclanthology.org/W18-6436
%U https://doi.org/10.18653/v1/W18-6436
%P 578-587

Markdown (Informal)

[Fine-grained evaluation of German-English Machine Translation based on a Test Suite](https://aclanthology.org/W18-6436) (Macketanz et al., 2018)

• Fine-grained evaluation of German-English Machine Translation based on a Test Suite (Macketanz et al., 2018)

ACL

• Vivien Macketanz, Eleftherios Avramidis, Aljoscha Burchardt, and Hans Uszkoreit. 2018. Fine-grained evaluation of German-English Machine Translation based on a Test Suite. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers, pages 578–587, Belgium, Brussels. Association for Computational Linguistics.