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Corpus preparation for low-resource languages and for development of humanlanguage technology to analyze or computationally process them is a laborioustask, primarily due to the unavailability of expert linguists who are nativespeakers of these languages and also due to the time and resources required.Bhojpuri, Magahi, and Maithili, languages of the Purvanchal region of India (inthe north-eastern parts), are low-resource languages belonging to theIndo-Aryan (or Indic) family. They are closely related to Hindi, which is arelatively high-resource language, which is why we compare with Hindi. Wecollected corpora for these three languages from various sources and cleanedthem to the extent possible, without changing the data in them. The textbelongs to different domains and genres. We calculated some basic statisticalmeasures for these corpora at character, word, syllable, and morpheme levels.These corpora were also annotated with parts-of-speech (POS) and chunk tags.The basic statistical measures were both absolute and relative and wereexptected to indicate of linguistic properties such as morphological, lexical,phonological, and syntactic complexities (or richness). The results werecompared with a standard Hindi corpus. For most of the measures, we tried tothe corpus size the same across the languages to avoid the effect of corpussize, but in some cases it turned out that using the full corpus was better,even if sizes were very different. Although the results are not very clear, wetry to draw some conclusions about the languages and the corpora. For POStagging and chunking, the BIS tagset was used to manually annotate the data.The POS tagged data sizes are 16067, 14669 and 12310 sentences, respectively,for Bhojpuri, Magahi and Maithili. The sizes for chunking are 9695 and 1954sentences for Bhojpuri and Maithili, respectively.

Linguistic Resources for Bhojpuri, Magahi and Maithili: Statistics about them, their Similarity Estimates, and Baselines for Three Applications