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A spelling similarity measure for cognate identification.

Project description

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
$ 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
$ 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
[Gomes2011]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,

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