|Appears in Collections:||Literature and Languages Conference Papers and Proceedings|
|Peer Review Status:||Refereed|
|Title:||Automatic Construction of Discourse Corpora for Dialogue Translation|
|Citation:||Wang L, Zhang X, Tu Z, Liu Q & Way A (2016) Automatic Construction of Discourse Corpora for Dialogue Translation In: Calzolari N, Choukri K, Declerck T, Goggi S, Grobelnik M, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S (ed.) LREC 2016, Tenth International Conference on Language Resources and Evaluation Proceedings, Paris: European Language Resources Association. LREC 2016, Tenth International Conference on Language Resources and Evaluation, 23.5.2016 - 28.5.2016, Portorož, Slovenia, pp. 2748-2854.|
|Conference Name:||LREC 2016, Tenth International Conference on Language Resources and Evaluation|
|Conference Location:||Portorož, Slovenia|
|Abstract:||In this paper, a novel approach is proposed to automatically construct parallel discourse corpus for dialogue machine translation. Firstly, the parallel subtitle data and its corresponding monolingual movie script data are crawled and collected from Internet. Then tags such as speaker and discourse boundary from the script data are projected to its subtitle data via an information retrieval approach in order to map monolingual discourse to bilingual texts. We not only evaluate the mapping results, but also integrate speaker information into the translation. Experiments show our proposed method can achieve 81.79% and 98.64% accuracy on speaker and dialogue boundary annotation, and speaker-based language model adaptation can obtain around 0.5 BLEU points improvement in translation qualities. Finally, we publicly release around 100K parallel discourse data with manual speaker and dialogue boundary annotation.|
|Status:||Book Chapter: publisher version|
|Rights:||The LREC 2016 Proceedings are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License|
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.