How to improve digital translation tools

Abstract

The technologies we use to translate information between languages continue to evolve. For example, Google Translator, Toolkit, Skype translate content into over 130 languages. Multilingual Information Search (CLIR) software (such as Google Search) allows users to search information in one language and get results in multiple languages at once. Social media platforms like Facebook provide instant translation of messages, so content that was once limited to a specific audience is now more accessible. While these digital translation tools certainly provide more options and resources for people who want to interact in different languages on the Internet, users can still face challenges. Digital translation software is developed using machine algorithms that primarily measure grammatical and lexical accuracy rather than relying on user experience research. Most modern digital translation tools operate on a translation­as­replacement model. Users enter a word or phrase in one language, select the desired target language, and click Translate. An equivalent word (or a set of equivalent words) in the target language appears on the screen.

The reliance on machine algorithms and the lack of user experience research conducted through digital translation have left large gaps in the capabilities of this software. To improve digital translation tools, we need to understand how users navigate the language on the Internet during their daily activities, as they incorporate cultural knowledge and localized experience into their translations.

References

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