Skip to main content

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 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
[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, http://www.springerlink.com/content/gtl56j3l06906020/

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

spsim-0.1.2.tar.gz (6.0 kB view details)

Uploaded Source

Built Distribution

spsim-0.1.2-py3-none-any.whl (8.6 kB view details)

Uploaded Python 3

File details

Details for the file spsim-0.1.2.tar.gz.

File metadata

  • Download URL: spsim-0.1.2.tar.gz
  • Upload date:
  • Size: 6.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for spsim-0.1.2.tar.gz
Algorithm Hash digest
SHA256 94675d3f7bda25736c78ad9e4edc46ae8b5d3f13fd5f65b4e5bb2766e95b3d05
MD5 0e576b0cf3955b608a2677a57dac961c
BLAKE2b-256 d0f231daa2857219050642144414ec57f04276da043d0024c1022c7647398d6b

See more details on using hashes here.

File details

Details for the file spsim-0.1.2-py3-none-any.whl.

File metadata

File hashes

Hashes for spsim-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 9665ba72f264276755791a97962f9daa1659e321add37563210c8942c9789ba9
MD5 0565da7d0a4b8b0861b24a211580809c
BLAKE2b-256 a5a8642e38b3ff64c6a3467463b1ae6ce94069e008b5028d0ff6f7f5250c5247

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page