# Extracting an English-Persian Parallel Corpus from Comparable Corpora

arXiv: https://arxiv.org/abs/1711.00681 · HTML: https://mlsanity.com/paper/1711.00681/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Nov 2017.

## Built on by (most cited first, 4 of 4)

- [Extending LLMs to New Languages: A Case Study of Llama and Persian Adaptation](https://mlsanity.com/paper/2412.13375/) (2024)
- [An Evaluation of Persian-English Machine Translation Datasets with Transformers](https://mlsanity.com/paper/2302.00321/) (2023)
- [Learning How to Translate North Korean through South Korean](https://mlsanity.com/paper/2201.11258/) (2022)
- [Large Language Models for Persian  leftrightarrow  English Idiom Translation](https://mlsanity.com/paper/2412.09993/) (2024)

## Abstract (arXiv)

Parallel data are an important part of a reliable Statistical Machine Translation (SMT) system. The more of these data are available, the better the quality of the SMT system. However, for some language pairs such as Persian-English, parallel sources of this kind are scarce. In this paper, a bidirectional method is proposed to extract parallel sentences from English and Persian document aligned Wikipedia. Two machine translation systems are employed to translate from Persian to English and the reverse after which an IR system is used to measure the similarity of the translated sentences. Adding the extracted sentences to the training data of the existing SMT systems is shown to improve the quality of the translation. Furthermore, the proposed method slightly outperforms the one-directional approach. The extracted corpus consists of about 200,000 sentences which have been sorted by their degree of similarity calculated by the IR system and is freely available for public access on the Web.