How AI Is Revolutionizing Buddhist Scriptures: Automatic Punctuation, OCR, and Translation

Longquan Temple, located at the foot of Phoenix Ridge, has become a leading research hub where monks combine Buddhist scholarship with modern technology. Xianchao, a former condensed‑matter physics master from Peking University, now heads the temple’s scripture office and leads AI‑driven projects on the DaZangJing (the Buddhist Tripitaka).

Automatic punctuation – The team built a Transformer‑based model that inserts modern Chinese punctuation (periods, commas, question marks, etc.) into ancient Buddhist texts without human intervention. Validation shows the model’s output is almost indistinguishable from human annotation, with the latest version reaching 93.3% accuracy.

To achieve this, they progressed from basic RNN sequence labeling to LSTM and finally incorporated ResNet residual networks, which boosted accuracy by 20‑30% over plain CNN approaches.

OCR and text recognition – Existing OCR tools target printed fonts and fail on classical scripts. Xianchao’s team developed a new engine based on a CNN+LSTM+CTC framework, training it on over 70,000 full‑page images and 1.68 million text‑line samples from the Korean edition of the Tripitaka. The system now supports single‑character, single‑column, and semi‑automatic multi‑column recognition, enabling large‑scale digitization.

Document alignment and translation – By constructing a parallel corpus of ancient and modern Chinese sentences, the team created an alignment algorithm that identifies mismatches using similarity and difference metrics, facilitating accurate modern‑language translations of Buddhist verses.

The automatic punctuation tool can process roughly 20,000 characters in a day, equating to about 300 CNY of traditional transcription fees, and even at a conservative 60% accuracy still generates significant economic value.

All tools are open‑source; the automatic punctuation service has been online since 2018 at gj.cool , offering a free API for researchers.

Future work aims to extend these AI techniques to other classical Chinese corpora such as the Confucian classics and historical records, allowing scholars to focus on higher‑level analysis rather than repetitive digitization tasks.

The team published a paper titled “When AI Meets Buddhism: The Compilation of the DaZangJing,” detailing their methodology and results.