VERTa: a linguistic approach to automatic machine translation evaluation.
Machine translation (MT) is directly linked to its evaluation in order to both compare different MT system outputs and analyse system errors so that they can be addressed and corrected. As a consequence, MT evaluation has become increasingly important and popular in the last decade, leading to the d...
| Publicado en: | Language Resources & Evaluation Vol. 53; no. 1; pp. 57 - 87 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Mar2019
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=135114244&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 135114244 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Mar2019 vid: 53 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 135114244 10.1007/s10579-018-9430-2 ppf: 57 ppct: 30 formats: fmt: – @attributes: type: T – @attributes: type: P size: 628KB tig: atl: VERTa: a linguistic approach to automatic machine translation evaluation. aug: au: Comelles, Elisabet Atserias, Jordi affil: Universitat de Barcelona, Gran Via de les Corts Catalanes 585, 08007, Barcelona, Spain University of the Basque Country, Paseo Manuel de Lardizábal, 1, 20018, Donosti, Spain su: Linguistics Translations Qualitative research Language & languages Semantics (Philosophy) sug: subj: Linguistics Translations Qualitative research Language & languages Semantics (Philosophy) keyword: Linguistic features Machine translation Machine translation evaluation MT metric Qualitative approach ab: Machine translation (MT) is directly linked to its evaluation in order to both compare different MT system outputs and analyse system errors so that they can be addressed and corrected. As a consequence, MT evaluation has become increasingly important and popular in the last decade, leading to the development of MT evaluation metrics aiming at automatically assessing MT output. Most of these metrics use reference translations in order to compare system output, and the most well-known and widely spread work at lexical level. In this study we describe and present a linguistically-motivated metric, VERTa, which aims at using and combining a wide variety of linguistic features at lexical, morphological, syntactic and semantic level. Before designing and developing VERTa a qualitative linguistic analysis of data was performed so as to identify the linguistic phenomena that an MT metric must consider (Comelles et al. 2017). In the present study we introduce VERTa's design and architecture and we report the experiments performed in order to develop the metric and to check the suitability and interaction of the linguistic information used. The experiments carried out go beyond traditional correlation scores and step towards a more qualitative approach based on linguistic analysis. Finally, in order to check the validity of the metric, an evaluation has been conducted comparing the metric's performance to that of other well-known state-of-the-art MT metrics. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2019. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2019 holdings: @attributes: islocal: N |
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