# Blur the Linguistic Boundary: Interpreting Chinese Buddhist Sutra in English via Neural Machine Translation

arXiv: https://arxiv.org/abs/2209.15164 · HTML: https://mlsanity.com/paper/2209.15164/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 24 references that are in the map.
- First posted on arXiv 30 Sep 2022.

## Builds on (most cited first, 13 of 13)

- [Language-agnostic BERT Sentence Embedding](https://mlsanity.com/paper/2007.01852/) (2020)
- [LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning](https://mlsanity.com/paper/2206.06522/) (2022)
- [Nearest Neighbor Machine Translation](https://mlsanity.com/paper/2010.00710/) (2020)
- [Facebook FAIR's WMT19 News Translation Task Submission](https://mlsanity.com/paper/1907.06616/) (2019)
- [Improving Sign Language Translation with Monolingual Data by Sign Back-Translation](https://mlsanity.com/paper/2105.12397/) (2021)
- [Translation Artifacts in Cross-lingual Transfer Learning](https://mlsanity.com/paper/2004.04721/) (2020)
- [Adaptive Nearest Neighbor Machine Translation](https://mlsanity.com/paper/2105.13022/) (2021)
- [Efficient Cluster-Based k-Nearest-Neighbor Machine Translation](https://mlsanity.com/paper/2204.06175/) (2022)
- [Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation](https://mlsanity.com/paper/1912.01214/) (2019)
- [Bilingual Dictionary Based Neural Machine Translation without Using Parallel Sentences](https://mlsanity.com/paper/2007.02671/) (2020)
- [A Survey on Low-Resource Neural Machine Translation](https://mlsanity.com/paper/2107.04239/) (2021)
- [nnSpeech: Speaker-Guided Conditional Variational Autoencoder for Zero-shot Multi-speaker Text-to-Speech](https://mlsanity.com/paper/2202.10712/) (2022)
- [Pronoun-Targeted Fine-tuning for NMT with Hybrid Losses](https://mlsanity.com/paper/2010.07638/) (2020)

## Abstract (arXiv)

Buddhism is an influential religion with a long-standing history and profound philosophy. Nowadays, more and more people worldwide aspire to learn the essence of Buddhism, attaching importance to Buddhism dissemination. However, Buddhist scriptures written in classical Chinese are obscure to most people and machine translation applications. For instance, general Chinese-English neural machine translation (NMT) fails in this domain. In this paper, we proposed a novel approach to building a practical NMT model for Buddhist scriptures. The performance of our translation pipeline acquired highly promising results in ablation experiments under three criteria.