| | --- |
| | dataset_info: |
| | features: |
| | - name: src_sent |
| | dtype: string |
| | - name: tgt_sent |
| | dtype: string |
| | - name: src_lang |
| | dtype: string |
| | - name: tgt_lang |
| | dtype: string |
| | - name: source |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 10784658 |
| | num_examples: 39994 |
| | download_size: 5255037 |
| | dataset_size: 10784658 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: data/train-* |
| | language: |
| | - en |
| | - uz |
| | - uzs |
| | pretty_name: lutfiy |
| | size_categories: |
| | - 10K<n<100K |
| | license: mit |
| | task_categories: |
| | - translation |
| | tags: |
| | - lutfiy |
| | - southern uzbek |
| | - afghani uzbek |
| | --- |
| | |
| | # Lutfiy: Southern Uzbek Parallel Corpus for Translation |
| |
|
| | This repository contains a parallel corpus for the Southern Uzbek language, developed as part of the research paper "Filling the Gap for Uzbek: Creating Translation Resources for Southern Uzbek". |
| |
|
| | ## Dataset Description |
| |
|
| | The Southern Uzbek Parallel Corpus is a collection of approximately 40,000 sentence pairs, designed to support machine translation tasks involving the Southern Uzbek language. It includes: |
| |
|
| | - Northern Uzbek - Southern Uzbek (37,415 pairs) |
| | - English - Southern Uzbek (2,579 pairs) |
| |
|
| | ## Usage |
| |
|
| | This dataset is intended for training and evaluating machine translation models involving the Southern Uzbek language. |
| |
|
| | To load and use dataset, run this script: |
| |
|
| | ```python |
| | from datasets import load_dataset |
| | |
| | lutfiy_corpus = load_dataset("tahrirchi/lutfiy", split='train') |
| | ``` |
| |
|
| | ## Dataset Structure |
| |
|
| | ### Data Instances |
| |
|
| | - **Size of downloaded dataset files:** 5.3 MB |
| | - **Size of the generated dataset:** 4.9 MB |
| | - **Total amount of disk used:** 10.2 MB |
| |
|
| | An example from the corpus looks as follows. |
| | ``` |
| | {'src_sent': "Bolakay ko'kka boqib, to'rg'ay hazratning boshi ustida aylanib sayrayotganini ko'rdi.", |
| | 'tgt_sent': 'بالهکهی کۉککه باقیب، تۉرغهی حرضتنینگ باشی اوستیده ایلهنیب َسیرهیاتگنینی کۉردی.', |
| | 'src_lang': 'uzn_Latn', |
| | 'tgt_lang': 'uzs_Arab', |
| | 'source': 'books'} |
| | ``` |
| |
|
| | ### Data Fields |
| |
|
| | The data fields are the same among all splits. |
| |
|
| | - `src_lang`: a `string` feature that contains source language. |
| | - `src_sent`: a `string` feature that contains sentence in source language. |
| | - `tgt_lang`: a `string` feature that contains target language. |
| | - `tgt_sent`: a `string` feature that contains sentence in target language. |
| | - `source`: a `string` feature that contains source information of the pair. |
| |
|
| | ## Data Sources |
| |
|
| | The corpus comprises diverse parallel texts sourced from multiple domains: |
| |
|
| | - 90% sentences from books (novels, non-fiction) |
| | - 6% sentences from internet websites |
| | - 4% sentences from bilingual dictionaries |
| |
|
| | ## Data Preparation |
| |
|
| | The data mining process involved local mining techniques, ensuring that parallel sentences were extracted from translations of the same book, document, or article. Sentence alignment was performed using LaBSE (Language-agnostic BERT Sentence Embedding) embeddings. For more information, plase refet to [our paper](https://arxiv.org/abs/2508.14586). |
| |
|
| | ## Citation |
| |
|
| | If you use this dataset in your research, please cite our paper: |
| |
|
| | ```bibtex |
| | @misc{mamasaidov2025fillinggapuzbekcreating, |
| | title={Filling the Gap for Uzbek: Creating Translation Resources for Southern Uzbek}, |
| | author={Mukhammadsaid Mamasaidov and Azizullah Aral and Abror Shopulatov and Mironshoh Inomjonov}, |
| | year={2025}, |
| | eprint={2508.14586}, |
| | archivePrefix={arXiv}, |
| | primaryClass={cs.CL}, |
| | url={https://arxiv.org/abs/2508.14586}, |
| | } |
| | ``` |
| | ## Contacts |
| |
|
| | We believe that this work will enable and inspire all enthusiasts around the world to open the hidden beauty of low-resource languages, in particular Southern Uzbek. |
| |
|
| | For further development and issues about the dataset, please use m.mamasaidov@tahrirchi.uz or a.shopolatov@tahrirchi.uz to contact. |