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

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arxiv 2001.09907 v1 pith:CYS7TNA4 submitted 2020-01-27 cs.CL

Barry Haddow , Faheem Kirefu This is my paper · ORCID
classification cs.CL
keywords corpuslanguagesparallelindiapairpmindiasentencesalignment
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 2 Pith papers

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  1. OpenLID-v3: Improving the Precision of Closely Related Language Identification -- An Experience Report

    cs.CL 2026-02 conditional novelty 5.0 of 10

    OpenLID-v3 matches or improves precision on closely related language identification by adding data, merging variants, and adding a noise class, while ensembling with GlotLID buys more precision at the cost of coverage.

  2. Analysis of Indic Language Capabilities in LLMs

    cs.CL 2025-01 conditional novelty 4.0 of 10

    A desk-research review finds that LLM performance is strongest for Hindi, Bengali, Marathi, Telugu, and Tamil, and recommends prioritizing these five languages for safety benchmarks.

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