Difference between revisions of "Task ideas for Google Code-in/Add words"

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(Created page with '# select a language pair, ideally such that the source language is a language you know (L₂) and the target language a language you use every day (L₁). # Install Apertium loca…')
 
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# select a language pair, ideally such that the source language is a language you know (L₂) and the target language a language you use every day (L₁).
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# Select a [[List of language pairs|language pair]], ideally such that the source language is a language you know (L₂) and the target language a language you use every day (L₁).
 
# Install Apertium locally from the Subversion repository; install the language pair; make sure that it works and/or get [http://wiki.apertium.org/wiki/Apertium_VirtualBox Apertium VirtualBox] and update, check out & compile the language pair.
 
# Install Apertium locally from the Subversion repository; install the language pair; make sure that it works and/or get [http://wiki.apertium.org/wiki/Apertium_VirtualBox Apertium VirtualBox] and update, check out & compile the language pair.
 
# Using a large enough corpus of representative text in the source language (e.g. plain text taken from Wikipedia, newspapers, literature, etc.) detect the 50 most frequent unknown words (source words which are not in the dictionaries of the language pair).
 
# Using a large enough corpus of representative text in the source language (e.g. plain text taken from Wikipedia, newspapers, literature, etc.) detect the 50 most frequent unknown words (source words which are not in the dictionaries of the language pair).

Revision as of 06:56, 8 December 2014

  1. Select a language pair, ideally such that the source language is a language you know (L₂) and the target language a language you use every day (L₁).
  2. Install Apertium locally from the Subversion repository; install the language pair; make sure that it works and/or get Apertium VirtualBox and update, check out & compile the language pair.
  3. Using a large enough corpus of representative text in the source language (e.g. plain text taken from Wikipedia, newspapers, literature, etc.) detect the 50 most frequent unknown words (source words which are not in the dictionaries of the language pair).
  4. add these words to the source dictionary (so that they are not unknown anymore), add the correspondence to the bilingual dictionary, and add the word to the target dictionary if not already there.
  5. Compile and test again
  6. Submit a patch to your mentor (or commit it if you have already gained developer access)