Aligning sentences in parallel corpora
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
A program for aligning sentences in bilingual corpora
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Introduction to Information Retrieval
Introduction to Information Retrieval
Constructing Parallel Corpus from Movie Subtitles
ICCPOL '09 Proceedings of the 22nd International Conference on Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy
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In this paper, we investigate the task of translating spontaneous speech transcriptions by employing aligned movie subtitles in training a statistical machine translator (SMT). In contrast to the lexical-based dynamic time warping (DTW) approaches to bilingual subtitle alignment, we align subtitle documents using time-stamps. We show that subtitle time-stamps in two languages are often approximately linearly related, which can be exploited for extracting high-quality bilingual subtitle pairs. On a small tagged data-set, we achieve a performance improvement of 0.21 F-score points compared to traditional DTW alignment approach and 0.39 F-score points compared to a simple line-fitting approach. In addition, we achieve a performance gain of 4.88 BLEU score points in spontaneous speech translation experiments using the aligned subtitle data obtained by the proposed alignment approach compared to that obtained by the DTW based alignment approach demonstrating the merit of the time-stamps based subtitle alignment scheme.