QUALESEstimación Automática de Calidad de Traducción Mediante Aprendizaje Automático Supervisado y No-Supervisado

  1. Calonge, Eusebi
  2. Martin, Maite
  3. Etchegoyhen, Thierry
  4. Martínez Garcia, Eva
  5. Azpeitia, Andoni
  6. Alegría Loinaz, Iñaki
  7. Labaka Intxauspe, Gorka
  8. Otegi, Arantza
  9. Sarasola Gabiola, Kepa
  10. Cortés Etxabe, Itziar
  11. Jauregi Carrera, Amaia
  12. Ellakuria, Igor
Journal:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Year of publication: 2018

Issue: 61

Pages: 143-146

Type: Article

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Abstract

The automatic quality estimation (QE) of machine translation consists in measuring the quality of translations without access to human references, usually via machine learning approaches. A good QE system can help in three aspects of translation processes involving machine translation and post-editing: increasing productivity (by ruling out poor quality machine translation), estimating costs (by helping to forecast the cost of post-editing) and selecting a provider (if several machine translation systems are available). Interest in this research area has grown significantly in recent years, leading to regular shared tasks in the main machine translation conferences and intense scientific activity. In this article we review the state of the art in this research area and present project QUALES, which is under development.

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