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Language use and
preservation online

    Tadej Gregorčič
“Minor” languages

• 6912+ languages altogether
• 3500 spoken by 0,2 % of world’s speakers
• 40% endangered
• Only 600 non-extinct within 100 years?
Endangered languages
Internet

• 90% of content in just 12 languages
• How big an issue is extinction?
• Language transformation vs. transformation
  of old media (TV, newspapers, radio)
• Unicode - first major breakthrough
Slovenian (my language)

• Roughly 2 million speakers
• More speakers than 96% of languages
• Official EU language - enforcement policies
• Endangerment?
Use of foreign words in scientific text where
 appropriate Slovenian counterparts exist.
Preservation of language
The Rosetta Project

• http://rosettaproject.org/
• Publicly accessible digital library
• Aiming to preserve information about
  eventually all human languages
Preservation of knowledge
   contained in a language
• Smithsonian Institute
• Rosetta Project
• Unesco
• Revitalization (non-extinct)
• Resurrection (extinct)
 • Only successful known example: Hebrew
Keeping use of a language
   viable/economical

• Consistent use
• Dictionaries, tools
• Translation tools
• Advanced language software (TTS, SR)
Language technologies
• Machine translation
• Speech synthesis
• Speech recognition
• ...
• Advance in one field accelerates advances
  in others through increased feasibility
Language technologies
• Machine translation
• Speech synthesis
• Speech recognition
• ...
• Advance in one field accelerates advances
  in others through increased feasibility
2005

• Systran (fr.)
• Yahoo!, Altavista Babelfish
• Google
• Rule based + statistical approach
Live translation
• Done in 2005 as Ethnocon project
  (presented at MS Imagine Cup)
• Speech recognition (language 1)
• Text machine translation (Systran API)
• Speech synthesis (language 2)
• MT quality poor
2006+
• Google Translate Systran
• Google obtained United Nations parallel
  corpora
• Words = data, grammar = code
• Purely statistical approach (a huge amount
  of data, code )
Parallel corpus

• evrokorpus.gov.si
• Translation memory (Trados ipd.)
• TM from governmental institutions
• Open TM projects
• ...
Parallel corpus

• evrokorpus.gov.si
• Translation memory (Trados ipd.)
• TM from governmental institutions
• Open TM projects
• Example: the Bible
Google Translate
Crowdsourcing


• It works (Wikipedia)
• An incorrect translation is a natural
  motivator
• Relatively fast improvement of data
• But: unprofessional
June, 2009
Google Translator Toolkit

• June, 2009 (200+ languages in October)
• “Open Trados”
• Global parallel TM
• Google TT + Google Translate
• 345 languages, 10.664 language pairs
Google Translator Toolkit

• Incentive for professionals: productivity
• Motivated to contribute to global TM
• GT pre-translates text with
• Huge parallel corpora
• Professional translation!
Professional translations are fed into the
 crowdsourced Google Translate parallel
                corpora.

Like Wikipedia with professional editors.

 Huge quality gains over time if Google
      Translator Toolkit takes off.
Results today:
Automatic subtitling




(think hearing impaired users)
Results soon:
AR, “augmented reality”
November 2009




Thank you!

Tadej Gregorcic
Software developer, entrepreneur and amateur linguist




twitter.com/tadej   linkedin.com/in/tadejgregorcic   www.facebook.com/tadej

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Language Use And Preservation Online