mlsanityData to 14 Oct 2026

KazParC: Kazakh Parallel Corpus for Machine Translation

arXiv 2403.19399 ↗First posted 28 Mar 2024cs.CLcited by 5

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Abstract (arXiv)

We introduce KazParC, a parallel corpus designed for machine translation across Kazakh, English, Russian, and Turkish. The first and largest publicly available corpus of its kind, KazParC contains a collection of 371,902 parallel sentences covering different domains and developed with the assistance of human translators. Our research efforts also extend to the development of a neural machine translation model nicknamed Tilmash. Remarkably, the performance of Tilmash is on par with, and in certain instances, surpasses that of industry giants, such as Google Translate and Yandex Translate, as measured by standard evaluation metrics, such as BLEU and chrF. Both KazParC and Tilmash are openly available for download under the Creative Commons Attribution 4.0 International License (CC BY 4.0) through our GitHub repository.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 8 of its 58 references that are in the map. First posted on arXiv 28 Mar 2024.

Builds on

8 of 58 references.

References · 8

  1. 2017Attention Is All You Needcited by 60,361
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  3. 2014Sequence to Sequence Learning with Neural Networkscited by 2,986
  4. 2022No Language Left Behind: Scaling Human-Centered Machine Translationcited by 1,312
  5. 2019Neural Machine Translation: A Review and Surveycited by 100
  6. 2017JESC: Japanese-English Subtitle Corpuscited by 16
  7. 2021KazNERD: Kazakh Named Entity Recognition Datasetcited by 15
  8. 2022KazakhTTS2: Extending the Open-Source Kazakh TTS Corpus With More Data, Speakers, and Topicscited by 10

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 0; 2026: 3.

5 papers.