  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.
