# PMIndia -- A Collection of Parallel Corpora of Languages of India

arXiv: https://arxiv.org/abs/2001.09907 · HTML: https://mlsanity.com/paper/2001.09907/

## Key facts

- Cited by 42 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jan 2020.

## Built on by (most cited first, 30 of 42)

- [MADLAD-400: A Multilingual And Document-Level Large Audited Dataset](https://mlsanity.com/paper/2309.04662/) (2023)
- [MuRIL: Multilingual Representations for Indian Languages](https://mlsanity.com/paper/2103.10730/) (2021)
- [Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages](https://mlsanity.com/paper/2104.05596/) (2021)
- [AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing](https://mlsanity.com/paper/2108.05542/) (2021)
- [Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages](https://mlsanity.com/paper/2212.05409/) (2022)
- [Survey of Low-Resource Machine Translation](https://mlsanity.com/paper/2109.00486/) (2021)
- [Building Machine Translation Systems for the Next Thousand Languages](https://mlsanity.com/paper/2205.03983/) (2022)
- [NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages](https://mlsanity.com/paper/2205.15960/) (2022)
- [MURAL: Multimodal, Multitask Retrieval Across Languages](https://mlsanity.com/paper/2109.05125/) (2021)
- [IndicBART: A Pre-trained Model for Indic Natural Language Generation](https://mlsanity.com/paper/2109.02903/) (2021)
- [Many-to-English Machine Translation Tools, Data, and Pretrained Models](https://mlsanity.com/paper/2104.00290/) (2021)
- [IndicXNLI: Evaluating Multilingual Inference for Indian Languages](https://mlsanity.com/paper/2204.08776/) (2022)
- [Pre-Trained Multilingual Sequence-to-Sequence Models: A Hope for Low-Resource Language Translation?](https://mlsanity.com/paper/2203.08850/) (2022)
- [ProxyLM: Predicting Language Model Performance on Multilingual Tasks via Proxy Models](https://mlsanity.com/paper/2406.09334/) (2024)
- [Itihasa: A large-scale corpus for Sanskrit to English translation](https://mlsanity.com/paper/2106.03269/) (2021)
- [SMOL: Professionally translated parallel data for 115 under-represented languages](https://mlsanity.com/paper/2502.12301/) (2025)
- [PMIndiaSum: Multilingual and Cross-lingual Headline Summarization for Languages in India](https://mlsanity.com/paper/2305.08828/) (2023)
- [Improving Machine Translation with Phrase Pair Injection and Corpus Filtering](https://mlsanity.com/paper/2301.08008/) (2023)
- [Improving Multilingual Neural Machine Translation System for Indic Languages](https://mlsanity.com/paper/2209.13279/) (2022)
- [Leveraging Auxiliary Domain Parallel Data in Intermediate Task Fine-tuning for Low-resource Translation](https://mlsanity.com/paper/2306.01382/) (2023)
- [OpenLID-v3: Improving the Precision of Closely Related Language Identification -- An Experience Report](https://mlsanity.com/paper/2602.13139/) (2026)
- [Unsupervised Machine Translation On Dravidian Languages](https://mlsanity.com/paper/2103.15877/) (2021)
- [AxomiyaBERTa: A Phonologically-aware Transformer Model for Assamese](https://mlsanity.com/paper/2305.13641/) (2023)
- [MILPaC: A Novel Benchmark for Evaluating Translation of Legal Text to Indian Languages](https://mlsanity.com/paper/2310.09765/) (2023)
- [Decoding the Diversity: A Review of the Indic AI Research Landscape](https://mlsanity.com/paper/2406.09559/) (2024)
- [Parallel Corpora for Machine Translation in Low-resource Indic Languages: A Comprehensive Review](https://mlsanity.com/paper/2503.04797/) (2025)
- [When Flores Bloomz Wrong: Cross-Direction Contamination in Machine Translation Evaluation](https://mlsanity.com/paper/2601.20858/) (2026)
- [Cost-Effective Training in Low-Resource Neural Machine Translation](https://mlsanity.com/paper/2201.05700/) (2022)
- ["A Little is Enough": Few-Shot Quality Estimation based Corpus Filtering improves Machine Translation](https://mlsanity.com/paper/2306.03507/) (2023)
- [Exploiting Domain-Specific Parallel Data on Multilingual Language Models for Low-resource Language Translation](https://mlsanity.com/paper/2412.19522/) (2024)

## Abstract (arXiv)

Parallel text is required for building high-quality machine translation (MT) systems, as well as for other multilingual NLP applications. For many South Asian languages, such data is in short supply. In this paper, we described a new publicly available corpus (PMIndia) consisting of parallel sentences which pair 13 major languages of India with English. The corpus includes up to 56000 sentences for each language pair. We explain how the corpus was constructed, including an assessment of two different automatic sentence alignment methods, and present some initial NMT results on the corpus.