Machine Translation Verbosity Control for Automatic Dubbing
This addresses the challenge of generating translations that fit timing constraints in automatic dubbing, which is incremental as it builds on existing methods for verbosity control.
The paper tackled the problem of controlling machine translation verbosity to improve automatic dubbing quality by matching translation duration to original utterances, reporting results from subjective tests on dubbed video clips in multiple languages.
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.