Automatic sentence segmentation and punctuation prediction for spoken language translation.
Evgeny Matusov, Arne Mauser, Hermann Ney · RWTH Publications (RWTH Aachen) · 2006
This paper studies the impact of automatic sentence segmentation and punctuation prediction on the quality of machine translation of automatically recognized speech.We present a novel sentence segmentation method which is specifically tailored to the requirements of machine translation algorithms and is competitive with state-of-the-art approaches for detecting sentence-like units.We also describe and compare three strategies for predicting punctuation in a machine translation framework, including the simple and effective implicit punctuation generation by a statistical phrase-based machine translation system.Our experiments show the robust performance of the proposed sentence segmentation and punctuation prediction approaches on the IWSLT Chinese-to-English and TC-STAR English-to-Spanish speech translation tasks in terms of translation quality.