Une archive numérique francophone des articles de recherche en Traitement Automatique de la Langue.

Investigating gender adaptation for speech translation

Rachel Bawden, Guillaume Wisniewski, Hélène Maynard

Abstract : In this paper we investigate the impact of the integration of context into dialogue translation. We present a new contextual parallel corpus of television subtitles and show how taking into account speaker gender can significantly improve machine translation quality in terms of B LEU and M ETEOR scores. We perform a manual analysis, which suggests that these improvements are not necessary related to the morphological consequences of speaker gender, but to more general linguistic divergences.

Keywords : Speech translation, SMT, gender, adaptation, parallel corpus.