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The ML4HMT Workshop on Optimising the Division of Labour in Hybrid Machine Translation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10130040" target="_blank" >RIV/00216208:11320/12:10130040 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    The ML4HMT Workshop on Optimising the Division of Labour in Hybrid Machine Translation

  • Original language description

    We describe the "Shared Task on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid Machine Translation" (ML4HMT) which aims to foster research on improved system combination approaches for machine translation (MT). Participants of the challenge are requested to build hybrid translations by combining the output of several MT systems of different types. We ?rst describe the ML4HMT corpus used in the shared task, then explain the XLIFF-based annotation format we have designedfor it, and brie?y summarize the participating systems. Using both automated metrics scores and extensive manual evaluation, we discuss the individual performance of the various systems. An interesting result from the shared task is the fact that we were able to observe different systems winning according to the automated metrics scores when compared to the results from the manual evaluation. We conclude by summarising the ?rst edition of the challenge and by giving an outlook to future

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2012

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC 2012)

  • ISBN

    978-2-9517408-7-7

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    3430-3435

  • Publisher name

    European Language Resources Association

  • Place of publication

    ?stanbul, Turkey

  • Event location

    ?stanbul, Turkey

  • Event date

    May 21, 2012

  • Type of event by nationality

    CST - Celostátní akce

  • UT code for WoS article