Record your voice. Earn $SLC + USDC. Teach AI your language. The dataset you can’t scrape, already training frontier AI models. Join 2.5M+ in 180 countries 🌍
USA
- Tweets 2,750
- Following 197
- Followers 153,589
- Likes 8,765
Monthly Raffle is upon us!
The final 4 words are in.
(Same Procedure as every month)
Each vote count is turned into a number and combined into one string and hashed with SHA-256 to generate a provably random seed. That seed selects the winners.
Vote now 📷
35%
Accent
27%
Dialect
22%
Acoustic
15%
Dawn
328 votes • 9 hours
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Filipino-accented English. One public benchmark. Leading ASR systems: 10.8% to 44.7% word error rate.
Same accent, same test.
Choose your model on the accents your users have. What we heard at Interspeech 2026: silencio.network/updates
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Before you trust a headline word error rate, ask two questions.
Who was speaking?
Were they reading?
Then build a test set that sounds like your users. silencio.network/updates
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Today is Uzbek Language Day.
33 million speakers across Central Asia. Barely represented in public speech data.
If you speak Uzbek, yours is one of the voices AI has hardly heard. Record a clip. Change that.
silencio.network
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Silencio is proud to support @Blockworks comment letter to the SEC on Regulation Crypto Assets.
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Who recorded our Kenyan Swahili sample?
103 speakers, one clip each. 66 from Nairobi, where Sheng runs through everyday Swahili. 26 from Mombasa, on the coast.
Unscripted answers, recorded on their own devices, every clip human-transcribed.
huggingface.co/datasets/Sile…
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Myth: AI understands every language.
Around 7,000 languages exist. Strong speech models handle a small fraction of them at production quality.
The gap is not technology. It is whether anyone recorded the language in the first place.
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Every clip in our catalogue is recorded by a real person in their own environment: homes, streets and workplaces from Lagos to the Visayas to Addis Ababa.
That is the acoustic world voice AI is deployed into.
It is rarely the one it is tested on.
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What language or dialect in your family is at risk of being left out of AI forever?
Reply. We want to hear which ones people are worried about.
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Code-switching is where voice assistants break.
Hindi to English and back, mid-sentence. People do it without noticing. Models trained on one language at a time notice every time.
It is almost never read aloud, so it has to be recorded the way people talk. We collect it to spec.
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Our speech data is recorded by ~2.5M contributors across ~180 countries, on their own phones, where they live and work.
Each one is paid per recording, with a consent record for every speaker.
That is why the accents in it are the accents real users have.
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Your Voice is the missing Data.
Check campaigns available for you: ai.silencio.store/
How do you say "hello" in your language?
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English is not one accent.
Our Accents of English sample on Hugging Face: 282 speakers born in 35 countries, 513 clips, 9.3 hours. Every clip labelled with country of birth, first language and accent.
Behind it: more than 100,000 hours off the shelf.
huggingface.co/datasets/Sile…
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Silencio | Voice Data for AI retweeted
Dear Silencians, please help us with our Wolof data collection and tag any crypto X communities from Senegal! @silencioNetwork
OR share the ongoing Wolof project with these communities, using your referral code, and you can earn referral commissions!!
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The final 4 words are in.
(Same Procedure as every month)
Each vote count is turned into a number and combined into one string and hashed with SHA-256 to generate a provably random seed. That seed selects the winners.
Vote now ⬇️
46%
Technology
17%
Responsibility
18%
Strength
19%
Chocolate
89 votes • Final results
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Final day, Interspeech 2026.
The data we brought here belongs to you. Every recording, every language, every voice on this network.
Thank you for making this possible. Looking forward to what we build together next.
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