A Sentence Meaning Based Alignment Method for Parallel Text Corpora Preparation
Abstract
Text alignment is crucial to the accuracy of Machine Translation (MT) systems, some NLP tools or any other text processing tasks requiring bilingual data. This research proposes a language independent sentence alignment approach based on Polish (not position-sensitive language) to English experiments. This alignment approach was developed on the TED Talks corpus, but can be used for any text domain or language pair. The proposed approach implements various heuristics for sentence recognition. Some of them value synonyms and semantic text structure analysis as a part of additional information. Minimization of data loss was ensured. The solution is compared to other sentence alignment implementations. Also an improvement in MT system score with text processed with described tool is shown.
Cite
@article{arxiv.1509.09093,
title = {A Sentence Meaning Based Alignment Method for Parallel Text Corpora Preparation},
author = {Krzysztof Wołk and Krzysztof Marasek},
journal= {arXiv preprint arXiv:1509.09093},
year = {2015}
}
Comments
corpora filtration, text alignement, corpora improvement. arXiv admin note: text overlap with arXiv:1509.08881