Automatic dubbing aims at seamlessly replacing the speech in a video document with synthetic speech in a different language. The task implies many challenges, one of which is generating translations that not only convey the original content, but also match the duration of the corresponding utterances. In this paper, we focus on the problem of controlling the verbosity of machine translation output, so that subsequent steps of our automatic dubbing pipeline can generate dubs of better quality. We propose new methods to control the verbosity of MT output and compare them against the state of the art with both intrinsic and extrinsic evaluations. For our experiments we use a public data set to dub English speeches into French, Italian, German and Spanish. Finally, we report extensive subjective tests that measure the impact of MT verbosity control on the final quality of dubbed video clips.
@article{arxiv.2110.03847,
title = {Machine Translation Verbosity Control for Automatic Dubbing},
author = {Surafel M. Lakew and Marcello Federico and Yue Wang and Cuong Hoang and Yogesh Virkar and Roberto Barra-Chicote and Robert Enyedi},
journal= {arXiv preprint arXiv:2110.03847},
year = {2021}
}
Comments
Accepted at IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021