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Celebrating International Translation Day: Meet 3 linguistic experts behind Google Translate

On International Translation Day, learn how members of our team bring cultural nuance to Translate to connect people globally.

Celebrating International Translation Day: Meet 3 linguistic experts behind Google Translate

International Translation Day celebrates the work of linguistic experts who enable communication across languages. Google Translate has been breaking down language barriers for over two decades. This year, three Googlers are highlighted who bridge cutting-edge technology with human connection.

Janneke's passion for language began in 2002 when she started teaching at an international university in Lithuania. Her academic work on African American language won the Linguistic Society of America's Leonard Bloomfield Book Award. At Google Translate, she leads the team testing new features to ensure translations reflect real human conversation. Her research on language evolution informs the Gemini models powering translations.

Isaac's interest in languages stems from growing up in Ireland's Gaeltacht region. After joining Google Translate in 2017, he expanded support for underrepresented languages, adding 146 new languages to the platform. He builds transliteration tools for speakers of languages with limited digital data, and has worked with communities to preserve native languages. Isaac emphasizes that AI cannot replace the human experience of speaking a different language.

Harsh has shaped foundational language tools at Google since 2018, including accent-tailored pronunciation guides and Search's grammar checker. His focus is on linguistic context to provide accurate translations, not just literal definitions. Working with human experts, he fine-tunes large language models to capture the nuanced meaning behind the words. By combining AI with linguistic expertise, Harsh aims to make Google Translate a smarter, culturally grounded tool for learning languages worldwide.

Written by urgent.news from Google Blog's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

Read the original at blog.google →

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