  In this paper, we introduce a divide-and-conquer algorithm to improve
sentence alignment speed. We utilize external bilingual sentence embeddings to
find accurate hard delimiters for the parallel texts to be aligned. We use
Monte Carlo simulation to show experimentally that using this
divide-and-conquer algorithm, we can turn any quadratic time complexity
sentence alignment algorithm into an algorithm with average time complexity of
O(NlogN). On a standard OCR-generated dataset, our method improves the
Bleualign baseline by 3 F1 points. Besides, when computational resources are
restricted, our algorithm is faster than Vecalign in practice.
