CUNI Experiments for WMT17 Metrics Task

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10372161" target="_blank" >RIV/00216208:11320/17:10372161 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

CUNI Experiments for WMT17 Metrics Task

Original language description

In this report paper we propose three different methods for automatic evaluation of the machine translation (MT) quality. Two of the metrics are trainable on direct-assessment scores and two of them use dependency structures. The trainable metric AutoDA, which uses deep-syntactic features, achieved better correlation with humans compared e.g. to the chrF3 metric.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

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

Project

<a href="/en/project/EF16_013%2F0001781" target="_blank" >EF16_013/0001781: LINDAT/CLARIN - Research infrastructure for language technologies - extension of the repository and its computational power</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

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

Article name in the collection

Proceedings of the Second Conference on Machine Translation, Volume 2: Shared Task Papers

ISBN

978-1-945626-96-8

ISSN

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e-ISSN

neuvedeno

Number of pages

8

Pages from-to

604-611

Publisher name

Association for Computational Linguistics

Place of publication

Stroudsburg, PA, USA

Event location

København, Denmark

Event date

Sep 7, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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