How to choose a suitable NMT solution? Evaluation of MT quality

• Caroline Rossi ^[1] ; Alice Carré ^[1]
  1. [1] Université Grenoble-Alpes
• Localización: Machine translation for everyone: empowering users in the age of artificial intelligence / coord. por Dorothy Kenny, 2022, ISBN 978-3-98554-045-7, págs. 51-79
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Machine translation (MT) is evolving fast, and there is no one-size-fits-all solution. In order to choose the right solution for a given project, users need to compare and assess different possibilities. This is never easy, especially with MT outputs that look increasingly good, thus making mistakes harder to spot. How can we best define and assess the quality of a neural MT solution, so as to make the right choices? The first step is certainly to define needs as precisely as possible. Having defined a pragmatic view of quality, we introduce the key notions in human and automatic evaluation of MT quality and outline how they can be applied by translators