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Google Adds Editing Tools to Online Translation

11 June 2009One Comment

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Google has brought out a translator toolkit that combines the company’s machine translation technology with online tools for manually editing content.

An earlier product, Google translate, allowed users to translate and read websites and plain text in a number of languages. The new translator toolkit targets users who want to edit and polish the translated text, and share or publish it.

Google’s statistical machine translation technology is trained using parallel streams of text in both the original language and the target language. Editing of machine translated text by users of the translator toolkit will help train the machine translation technology to a higher degree of accuracy.

Google’s Indian R&D lab developed the new product, which is the latest of a number of tools developed by Google in India to improve access to content in local languages.

The translator toolkit supports 47 languages, including five Indian languages.

Instead of re-creating content in local languages, Google translate and the translator toolkit allows people to translate existing content.

By an arrangement with Wikipedia, users can download a Wikipedia entry into the translator toolkit, translate it into a local language using machine translation, correct and polish the translation and post it to the online encyclopedia.

Professional translators can also upload personal files to the translator toolkit, and use the toolkit provided by Google, which includes a glossary, and dictionary, among other features. The local file and the translation can be kept private.

A translation memory database in the toolkit provides lookups to previous translations of similar sentences and text.

The toolkit is likely to be useful to publishers of news sites who now can target new audiences with local language editions at a lower cost.

One Comment »

  • Kathleen said:

    So google gets smarter with the help of the Internet? Smart enough. I have noticed google translate has become better for some language pairs but then it goes bad again and then it is again good. Statistical method is what most use nowadays but other companies combine different methods to achieve good results like Interlecta for example, http://home.interlecta.com

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