For event organisers and AV teams
Baian translates live talks using context to follow the speaker’s meaning. At conferences, lectures and events, attendees read or listen on their own phones.
How often Baian was preferredOver professional translations · English into each language
The line marks 50%: an even split.
How it works
The microphone sends the speech to Baian. Baian turns it into text, translates the meaning, and sends it to the people following. The speaker carries on as usual.
From the sound desk to every outputOne stage feed. Several places it can go.
For your team
You need a laptop or tablet, a connection to your microphone or mixer, and internet.
Plug the sound desk into a laptop by USB, or use an audio interface.
Choose your languages and press start.
Attendees scan it and follow on their own phones.
For your audience
Scan the QR code and choose a language. They can read on their phone, or listen through headphones where audio is available. No app or account needed.
1. Scan
2. Choose a language
3. Listen or read
Engineered for accuracy
Baian uses the recent speech as context when it translates. We test the result against professional translations, as well as measuring how quickly the text appears.
Translation follows in about 2.4 seconds.Seconds behind the speaker. Lower is better.
Compared with interpreters
BaianRuns for the whole session.
InterpretersSwap about every 30 minutes.
BaianNo fatigue, however long it runs.
InterpretersIn one study, meaning errors rose after 30 minutes.
BaianBuilt to translate the speech, not summarise it.
InterpretersIn one study, omitted meaning in 350 of 590 segments.
BaianSeveral languages from one stage feed.
InterpretersOne interpreter team per language.
BaianThe speech and each translation, saved.
InterpretersSeparate transcription needed.
BaianDownload the translated audio afterwards.
InterpretersOnly if someone records the booth.
For AV teams
Yes. Send captions to venue screens and your livestream, or translated audio to an existing headset system.
Customer story · QIYADA, Doha
At Qatar Foundation’s QIYADA conference, attendees scanned the code and followed Arabic and English on their own phones. The interpreter booths were taken down.
Plan your event
Questions
No. They scan your QR code, choose a language and read or listen in their phone’s browser. They don’t need to create an account.
About 1 second for the speaker’s own words and 2.4 seconds for translated text, based on our recordings. These are feed estimates, not phone-screen measurements. The text can change as the speaker continues.
It can, if your event allows it. Try Baian with a recording of your own speakers first, and check any requirements for accredited interpreters. We can help you plan where to use Baian and where to keep a human interpreter.
Yes. Baian can send translated audio to your headset transmitters through an audio interface. Your AV team should test it on the real receivers before the day.
Events can plan for up to 10,000 listeners across several languages. Tell us your numbers before you book and we’ll confirm capacity and support.
We can’t put “zero errors” in the guarantee. (Psst. We like our chances.) Bring your own audio and put Baian to the test. We’ll check names, specialist terms and your sound feed before the event.
No. The laptop or tablet running Baian, and your audience’s phones, need an internet connection.
Listeners hear an AI voice today. Speaker voice cloning is experimental and coming soon.
Bring a short recording, your languages and your audience size. We’ll show you the listener experience.
Arrange a demo WhatsApp1st in Arabic (5.1%) and Korean (2.9%), 2nd in Russian and Danish. Fewer errors than all three OpenAI real-time models in 13 of the 14 languages we publish.
FLEURS: short Wikipedia sentences read aloud. Measures how many words come out wrong.
AssemblyAI published scores for 14 real-time engines. We ran Baian’s live interpreter on the same test set.
We joined clips into 15-minute recordings with 1.5-second gaps and played them into Baian’s live interpreter in real time, like a microphone, with automatic language detection. AssemblyAI streamed each clip separately with the language set in advance. Scoring ignores punctuation, capital letters, Arabic vowel marks and how numbers are written. Our charts show 13 of AssemblyAI’s 14 engines; the full table is on AssemblyAI’s site.
Caption Tool scored above the translators in Hausa, Swahili, Tamil and Urdu (preferred on 67% to 75% of sentences). Baian’s live interpreter had about the same overall quality in Arabic, Hindi and Korean.
148 English sentences that also have professional human translations. Measures translation quality with Google’s MetricX-24 automatic judge.
Baian ran the test. The human translations come from the public FLoRes-200 set.
Baian worked from the spoken audio; the translators worked from text. We compared scores sentence by sentence and counted a result only when the 95% range did not cross zero and two runs agreed. “About the same” means the test found no clear difference; it does not prove the translations were identical.
Median 2.1 seconds across 53 recordings in 15 languages (1.3 to 2.7 seconds per recording).
How long after a sentence ends its finished translation appears.
Baian, on its production Live service.
Measured on Baian’s production Live service from 13 to 15 October 2026, from the end of each spoken sentence to the finished English line in our captured listener feed. Earlier words in a long sentence wait longer than this. Spoken audio arrives a little after the text and was not measured.
Estimated medians: the speaker’s words appear in their own language about 1.0 seconds after they are spoken, and the first translation covering a word about 2.4 seconds after it.
Estimated from our captured listener feed for the same 53 recordings. The capture is incomplete, so some early previews are missing, and previews can still change before the sentence is finished. Times are measured to the feed, not to a phone screen.
Median 2.69 seconds behind the speaker, across 180 speeches.
About 30 minutes is the recommended turn. Meaning errors rose steadily after 30 minutes on task (pilot study, five professionals).
Part of the meaning was missing in 350 of 590 speech segments.