  Text alignment and text quality are critical to the accuracy of Machine
Translation (MT) systems, some NLP tools, and any other text processing tasks
requiring bilingual data. This research proposes a language independent
bi-sentence filtering approach based on Polish (not a position-sensitive
language) to English experiments. This cleaning approach was developed on the
TED Talks corpus and also initially tested on the Wikipedia comparable corpus,
but it can be used for any text domain or language pair. The proposed approach
implements various heuristics for sentence comparison. Some of them leverage
synonyms and semantic and structural analysis of text as additional
information. Minimization of data loss was ensured. An improvement in MT system
score with text processed using the tool is discussed.
