Investigating gender adaptation for speech translation
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.
PDF Abstract
Datasets
Add Datasets
introduced or used in this paper
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here
