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Article published In:
Intelligences pour la traduction. IA et interculturel : actions et interactions.
Edited by Ludovica Maggi and Sarah Bordes
[FORUM 20:2] 2022
► pp. 315–332

Evaluer, diagnostiquer et analyser la traduction automatique neuronale

| Université Paris-Saclay, CNRS, LISN

Les outils de traduction automatique (TA) neuronale ont fait des progrès sensibles, qui qui les rendent utilisables pour un nombre croissant de domaines et de couples de langues. Cette évolution majeure des technologies de traduction invite à revisiter les méthodes de mesure de la qualité de la traduction, en particulier des mesures dites automatiques, qui jouent un rôle fondamental pour orienter les nouveaux développements de ces systèmes. Dans cet article, nous dressons un état des lieux des méthodes utilisées dans le cycle de développement des outils de traduction automatique, depuis les évaluations purement quantitatives jusqu’aux méthodologies récemment proposées pour analyser et diagnostiquer le fonctionnement de ces “boites noires” neuronales.

Keywords: Traduction automatique neuronale, Evaluation de la traduction automatique, Métriques pour la traduction automatique
Article outline
  • 1.Introduction
  • 2.La TA Neuronale : Principes et concepts
    • 2.1Traduire par apprentissage
    • 2.2TAN : Traduction automatique numérique
    • 2.3Configurer Aθ: Le choix des méta-paramètres
  • 3.Métriques automatiques : Le rôle des références humaines
    • 3.1Les évaluations globales
    • 3.2Évaluer sans référence
  • 4.À la recherche des failles de la TA
    • 4.1Des bancs d’essais spécialisés
    • 4.2Évaluation par des manipulations linguistiques
      • 4.2.1Dans la phrase source
      • 4.2.2Dans la phrase cible
  • 5.Sous le capot, le moteur (de traduction)
    • 5.1Analyse des représentations (sondes linguistiques)
  • 6.Conclusion
  • Remarques
  • Bibliographie

Article language: French

Published online: 12 January 2023
DOI logo
https://doi.org/10.1075/forum.00023.yvo
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