A spelling similarity measure for cognate identification.
spsim is a Python 3 module that implements a spelling similarity measure for identifying cognates across languages, taking into account spelling differences that are characteristic of each language pair, as described in [Gomes2011].
Note: in the examples below, $ denotes the Bash prompt and a Linux, MacOs or similar *nix environment is assumed.
Install as usual:
$ pip3 install spsim
Example command line usage:
$ # first let's get some pairs of words that may be cognates: $ wget http://research.variancia.com/spsim/maybe_enpt.txt $ cat maybe_enpt.txt pharmacy farmácia arithmetic aritmética $ # If we don't give any example cognates, SpSim will be equivalent to $ # 1 - edit_distance / max_len_of_strings $ # Note that by default spsim matches accentuated characters, i.e. a == á $ echo "" > empty.txt $ spsim empty.txt maybe_enpt.txt pharmacy farmácia 0.5 arithmetic aritmética 0.8 $ now let's get some example cognates: $ wget http://research.variancia.com/spsim/examples_enpt.txt $ cat examples_enpt.txt alcohol álcool alpha alfa anomaly anomalia mathematics matemática methodology metodologia metric métrica morphine morfina photos fotos $ # by giving these examples to spsim, it will learn to ignore certain differences: $ spsim examples_enpt.txt maybe_enpt.txt pharmacy farmácia 1.0 arithmetic aritmética 1.0
Measuring Spelling Similarity for Cognate Identification, Luís Gomes and Gabriel Pereira Lopes in Progress in Artificial Intelligence, 15th Portuguese Conference in Artificial Intelligence, EPIA 2011, Lisboa, Portugal, October 2011, http://www.springerlink.com/content/gtl56j3l06906020/
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