We conducted a detailed analysis on the quality of web-mined corpora for two low-resource languages (making three language pairs, English-Sinhala, English-Tamil and Sinhala-Tamil). We ranked each corpus according to a similarity measure and carried out an intrinsic and extrinsic evaluation on different portions of this ranked corpus. We show that there are significant quality differences between different portions of web-mined corpora and that the quality varies across languages and datasets. We also show that, for some web-mined datasets, Neural Machine Translation (NMT) models trained with their highest-ranked 25k portion can be on par with human-curated datasets.

A word frequency list is a list of unique words in a language along with their frequency count. It is generally sorted by frequency. Such a list is essential for many NLP tasks, including building language models, POS taggers, spelling checkers, word separation guides, etc., in addition to assisting language learners. Such lists are available for many languages, but a large-scale word list is still not available for Sinhala. We have developed a comprehensive list of words, together with their frequency and part-of-speech (POS), from a large textbase. Unlike many other such lists, our list includes a large number of low-frequency words (many of which are erroneous), which enables the analysis of such words, including the frequencies of errors. In addition to the main list, we have also prepared a list of linguistically verified words. The word frequency list and the verified word list are the largest collections of words lists that are available for the Sinhala language.