Google Expands AI Language Support Beyond 300 Languages
Google has used AI and machine learning in Google Translate since its 2006 launch, moving language technology beyond word-for-word conversion toward systems that can interpret speech, emotion, tone and local slang. The effort is central to the company’s 1,000 Languages Initiative, which targets the world’s most widely spoken languages and aims to reduce barriers to education, jobs and digital services. Google said it has committed more than $1 billion to global training and skills programs, reaching over 100 million people.
On Sept. 15, 2026, Google said its technologies supported more than 300 languages spoken by roughly 7 billion people, or 86% of the global population. More than 1 billion users translate about 1 trillion words each month through Google Translate. The company also introduced Gemini 3.5 Live Translate, supporting 70 languages and more than 2,000 language pairs, and highlighted an open dataset developed with Makerere University, the University of Ghana and Digital Umuganda covering 27 African languages spoken by more than 100 million people.
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The history behind this eventGoogle Launches Gemini 3.5 Live Translate for Real-Time Speech Interpretation in More Than 70 Languages
Google is extending Gemini 3.5's generative AI capabilities to real-time interpretation through direct speech-to-speech translation that preserves a speaker's original tone, cadence and delivery. Compared with conventional systems that first convert speech into text before synthesizing audio, the new model can reduce pauses, making it significant for international meetings, travel and customer service communications.
Google has launched the Gemini 3.5 Live Translate audio model, which can translate more than 70 languages in real time. The model is being integrated into Google Translate and Google Meet and is also available in developer preview. Google has begun testing it with partners including Southeast Asian ride-hailing and delivery platform Grab to assess translation speed and naturalness in real-world service settings.
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