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First, automated summarization is indeed a task in computational linguistics, although I suspect (I'm not really close to that particular field) that they employ some neural networks now and no longer a rule-based system as sketched in the question. The sketch in the question also touches another important task in computational linguistics and natural ...


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The ideal answer for this question is: A corpus stays relevant forever once it is introduced into scientific study. There are now repositories for language data that are aiming to keep corpora available for a long time. For a more practical point of view, large research funding organisations (like DFG in Germany) demand keeping research data available for at ...


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Sound changes are not generally reversible and so it is, in general, impossible to produce a single unique cognate As an example, in Old English, i-mutation causes /e/ to merge into /i/ when followed by an /i/ that is earlier eCi iCi > iCi. As many final -i were lost, many i in final syllables could derive from an earlier e or an earlier i and so we would ...


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Phonetisaurus can do that: https://github.com/AdolfVonKleist/Phonetisaurus There is a strict 1-1 correspondence between the 2 rows: c l o s e <eps> K L OW1 Z _ <eps> q u o t e <eps> K W OW1 T _ <eps> Python code: import phonetisaurus model = phonetisaurus.Phonetisaurus ("../../train/model.fst") results = ...


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