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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

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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