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Google launches Gemini 3.5 Transcribe with smarter speech-to-text and 85+ language support

Google launches Gemini 3.5 Transcribe with smarter speech-to-text and 85+ language support

Google is pushing speech AI beyond basic dictation, with new capabilities designed to handle natural conversations, specialised vocabulary and multiple speakers while making transcripts more useful across its ecosystem.

Vidhya Das
Vidhya Das
  • Noida,
  • Updated Aug 27, 2026 12:00 PM IST
Google launches Gemini 3.5 Transcribe with smarter speech-to-text and 85+ language supportGoogle’s Gemini 3.5 Transcribe aims to deliver faster, more accurate speech-to-text across languages.

Google has introduced Gemini 3.5 Transcribe, which it describes as its most precise speech-to-text model yet. The model can clean up disfluencies, remove filler words, handle self-corrections and automatically format transcribed text. It can also recognise custom vocabulary, specialised jargon and unique spellings.

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Turning natural speech into clean, usable text can be difficult when conversations involve accents, background noise, specialised terms or people correcting themselves mid-sentence. Google is now addressing those challenges with a new model focused on making speech transcription more accurate and useful across a range of situations. 

Gemini 3.5 Transcribe focuses on accuracy

The technology is aimed at developers building voice agents and other audio-based applications, while Google is also bringing related capabilities to several of its own products. For users, the changes could make speaking to AI more practical by reducing the need to manually correct transcripts and helping spoken instructions translate into more structured text.

Gemini 3.5 Transcribe supports more than 85 languages, including accents and dialects. For recorded audio, it can identify up to three speakers and provide word-level timestamps. Support for more than three speakers is currently experimental.

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Google cites Artificial Analysis measurements showing a 4% average Word Error Rate (WER) for streaming and 2.6% for non-streaming use cases. Google also says the time to final transcription is 70% faster than Chirp 3. On the FLEURS benchmark, the model recorded 5.50% WER in streaming and 5.04% in non-streaming tests.

APIs and Google product integration

Developers can access the model through two APIs. The Live API supports continuous bidirectional streaming with sub-second latency, while the Interactions API is designed for recorded meetings, call logs and other audio, including speaker attribution and timestamps.

Google is also integrating the technology across its ecosystem. On Android, Gboard's Rambler can convert speech into formatted text and lets users make corrections or change writing style using voice. Google Antigravity can use screen context and chat history, with permission, to improve transcription accuracy.

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In Gemini's macOS app, voice commands can analyse local files, repurpose text, generate images and complete other workflows. Google AI Studio supports voice-based app building, while Chrome will soon support dictation into web fields.

Gemini 3.5 Transcribe is available in public preview through Google AI Studio and Google Antigravity. Enterprise access is available through Gemini Enterprise Agent Platform, while the Gemini macOS app supports it in English, and Rambler is available on Android in select countries and languages.

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ABOUT THE AUTHOR

Vidhya Das
Vidhya Das

Vidhya Das is a journalist who writes about technology, AI, startups and the digital world. With a background in Journalism and Mass Communication, she enjoys breaking down complex topics into simple, engaging stories. She is curious about how technology is changing everyday life and loves finding stories that matter.

Published on: Aug 27, 2026 12:00 PM IST