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Source language classification of indirect translations

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11210%2F22%3A10456674" target="_blank" >RIV/00216208:11210/22:10456674 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=SMT_u-XsKd" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=SMT_u-XsKd</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1075/target.00006.iva" target="_blank" >10.1075/target.00006.iva</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Source language classification of indirect translations

  • Original language description

    One of the major barriers to the systematic study of indirect translation - that is, translations of translations - is the lack of efficient methods to identify these translations. In this article, we use supervised machine learning to examine whether computers can be harnessed to identify indirect translations. Our data consist of a monolingual comparable corpus that includes (1) nontranslated Finnish texts, (2) direct translations from English, French, German, Greek, and Swedish into Finnish, and (3) indirect translations from Greek (the ultimate source language) via English, French, German, and Swedish (mediating languages) into Finnish. We use n-grams of various types and lengths as feature sets and random forests as the statistical classification technique. To maximize the transferability of the method, the feature sets were implemented in accordance with the Universal Dependencies framework. This study confirms that computers can distinguish between translated and nontranslated Finnish, as well as between Finnish translations made from different source languages. Regarding indirect translations, the ultimate source language has a greater impact on the linguistic composition of indirect Finnish translations than their respective mediating languages. Hence, the indirect translations could not be reliably identified. Therefore, our results suggest that the reliable computational identification of indirect translations and their mediating languages requires a way to control for the effect of the ultimate source language.

  • 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

    60203 - Linguistics

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Target

  • ISSN

    0924-1884

  • e-ISSN

    1569-9986

  • Volume of the periodical

    34

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    25

  • Pages from-to

    370-394

  • UT code for WoS article

    000782566300001

  • EID of the result in the Scopus database