The Ottoman-Turkish Transliteration using Traditional NLP Techniques

Ottoman-Turkish transliteration is a relatively new problem. To make a vast amount of historical documents, books, newspapers, and magazines accessible to a wider audience unfamiliar with the Ottoman script, it is necessary to transliterate the Ottoman script into the Latin-based Turkish script. This study employs traditional NLP techniques to develop a dictionary-based Ottoman-Turkish transliteration system. Using a dataset of 2403 sentences and 31K words, we achieved a Word Error Rate (WER) of 20.69% (raw), 6.31% (normalized) and a Character Error Rate (CER) of 6.46% (raw) 3.01% (normalized), resulting in a BLEU score of 51.90 (raw) 77.18 (normalized). The results show that the proposed system has a promising performance for Ottoman-Turkish transliteration.