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Most legal text in the Indian judiciary is written in complex English due tohistorical reasons. However, only about 10% of the Indian population iscomfortable in reading English. Hence legal text needs to be made available invarious Indian languages, possibly by translating the available legal text fromEnglish. Though there has been a lot of research on translation to and betweenIndian languages, to our knowledge, there has not been much prior work on suchtranslation in the legal domain. In this work, we construct the firsthigh-quality legal parallel corpus containing aligned text units in English andnine Indian languages, that includes several low-resource languages. We alsobenchmark the performance of a wide variety of Machine Translation (MT) systemsover this corpus, including commercial MT systems, open-source MT systems andLarge Language Models. Through a comprehensive survey by Law practitioners, wecheck how satisfied they are with the translations by some of these MT systems,and how well automatic MT evaluation metrics agree with the opinions of Lawpractitioners.

Improving Access to Justice for the Indian Population: A Benchmark for Evaluating Translation of Legal Text to Indian Languages