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MT Evaluation in the Context of Language Complexity

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F21%3A43920964" target="_blank" >RIV/62156489:43110/21:43920964 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216305:26210/22:PU143580

  • Result on the web

    <a href="https://doi.org/10.1155/2021/2806108" target="_blank" >https://doi.org/10.1155/2021/2806108</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1155/2021/2806108" target="_blank" >10.1155/2021/2806108</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    MT Evaluation in the Context of Language Complexity

  • Original language description

    The paper focuses on investigating the impact of artificial agent (machine translator) on human agent (posteditor) using a proposed methodology, which is based on language complexity measures, POS tags, frequent tagsets, association rules, and their summarization. We examine this impact from the point of view of language complexity in terms of word and sentence structure. By the proposed methodology, we analyzed 24 733 tags of English to Slovak translations of technical texts, corresponding to the output of two MT systems (Google Translate and the European Commission&apos;s MT tool). We used both manual (adequacy and fluency) and semiautomatic (HTER metric) MT evaluation measures as the criteria for validity. We show that the proposed methodology is valid based on the evaluation of frequent tagsets and rules of MT outputs produced by Google Translate or of the European Commission&apos;s MT tool, and both postedited MT (PEMT) outputs using baseline methods. Our results have also shown that PEMT output produced by Google Translate is characterized by more frequent tagsets such as verbs in the infinitive with modal verbs compared to its MT output, which is characterized by masculine, inanimate nouns in locative of singular. In the MT output, produced by the European Commission&apos;s MT tool, the most frequent tagset was verbs in the infinitive compared to its postedited MT output, where verbs in imperative and the second person of plural occurred. These findings are also obtained from the use of the proposed methodology for MT evaluation. The contribution of the proposed methodology is an identification of systematic not random errors. Additionally, the study can also serve as information for optimizing the translation process using postediting.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Complexity

  • ISSN

    1076-2787

  • e-ISSN

  • Volume of the periodical

    Neuveden

  • Issue of the periodical within the volume

    17 December

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    15

  • Pages from-to

    2806108

  • UT code for WoS article

    000783326400002

  • EID of the result in the Scopus database

    2-s2.0-85122366968