Parallel Text Alignment and Monolingual Parallel Corpus Creation from Philosophical Texts for Text Simplification

Text simplification is a growing field with many potential useful applications. Training text simplification algorithms generally requires a lot of annotated data, however there are not many corpora suitable for this task. We propose a new unsupervised method for aligning text based on Doc2Vec embeddings and a new alignment algorithm, capable of aligning texts at different levels. Initial evaluation shows promising results for the new approach. We used the newly developed approach to create a new monolingual parallel corpus composed of the works of English early modern philosophers and their corresponding simplified versions.