Abstract

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 …

Date

February 1, 2013

Authors

Andreas Tsiartas, Prasanta Ghosh, Panayiotis Georgiou, Shrikanth Narayanan

Journal

Computer Speech & Language

Volume

27

Issue

2

Pages

572-591

Publisher

Academic Press