Paper Info
Title
Machine Translation for Subtitling: A Large-Scale Evaluation.
Abstract
This article describes a large-scale evaluation of the use of Statistical Machine Translation for professional subtitling. The work was carried out within the FP7 EU-funded project SUMAT and involved two rounds of evaluation: a quality evaluation and a measure of productivity gain/loss. We present the SMT systems built for the project and the corpora they were trained on, which combine professionally created and crowd-sourced data. Evaluation goals, methodology and results are presented for the eleven translation pairs that were evaluated by professional subtitlers. Overall, a majority of the machine translated subtitles received good quality ratings. The results were also positive in terms of productivity, with a global gain approaching 40%. We also evaluated the impact of applying quality estimation and filtering of poor MT output, which resulted in higher productivity gains for filtered files as opposed to fully machine-translated files. Finally, we present and discuss feedback from the subtitlers who participated in the evaluation, a key aspect for any eventual adoption of machine translation technology in professional subtitling.
Year
Venue
Keywords
2014
LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
statistical machine translation,user evaluation,subtitling
Field
DocType
Citations 
Computer science,Machine translation,Filter (signal processing),Artificial intelligence,Natural language processing,Machine translated
Conference
2
PageRank 
References 
Authors
0.41
5
10
Name
Order
Citations
PageRank
Thierry Etchegoyhen186.70
Lindsay Bywood220.75
Mark Fishel36417.32
Panayota Georgakopoulou452.93
Jie Jiang520.41
Gerard van Loenhout620.41
Arantza del Pozo7308.34
Mirjam Sepesy Maučec850626.34
Anja Turner920.41
Martin Volk10399.90