Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/23457
Appears in Collections:Literature and Languages Conference Papers and Proceedings
Peer Review Status: Refereed
Authors: Wang, Longyue
Zhang, Xiaojun
Tu, Zhaopeng
Liu, Qun
Way, Andy
Contact Email: xiaojun.zhang@stir.ac.uk
Title: Automatic Construction of Discourse Corpora for Dialogue Translation
Editors: Calzolari, N
Choukri, K
Declerck, T
Goggi, S
Grobelnik, M
Maegaard, B
Mariani, J
Mazo, H
Moreno, A
Odijk, J
Piperidis, S
Citation: Wang L, Zhang X, Tu Z, Liu Q & Way A (2016) Automatic Construction of Discourse Corpora for Dialogue Translation, 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, LREC 2016, Tenth International Conference on Language Resources and Evaluation, Portorož, Slovenia, 23.5.2016 - 28.5.2016, Paris: European Language Resources Association, pp. 2748-2854.
Issue Date: 13-May-2016
Conference Name: LREC 2016, Tenth International Conference on Language Resources and Evaluation
Conference Dates: 2016-05-23T00:00:00Z
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.
Type: Conference Paper
Status: Book Chapter: publisher version
Rights: The LREC 2016 Proceedings are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
URI: http://hdl.handle.net/1893/23457
URL: http://www.lrec-conf.org/proceedings/lrec2016/index.html
Affiliation: Dublin City University
English Studies
Huawei Technologies (HK)
ADAPT Centre
ADAPT Centre

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