Can AI transcribe mixed Estonian-Russian customer conversations?

Yes. Modern speech recognition handles dialogues where the customer and the clerk speak different languages — or switch languages mid-conversation. VILFF was built in Estonia specifically for this environment: it transcribes Estonian, Russian, English and other languages, separates who said what, and shows the transcript with a translation in the portal.

Why mixed dialogues are hard

Classic speech-to-text expects one language per recording. Real shop-floor speech in Estonia is different: a customer asks in Russian, the clerk answers in Estonian, product names come in English, and single sentences mix all three. Add background noise, distance from the microphone and regional accents, and most generic tools fall apart.

How VILFF handles it

• Speaker separation — each utterance is attributed to the customer or the employee;
• Per-utterance language handling — the model does not force the whole conversation into one language;
• Translation in the portal — you read every dialogue in the portal language you choose (Estonian, English or Russian), with the original preserved;
• Noise-tolerant pipeline — voice-activity detection cuts silence and far-away speech, and low-confidence segments are re-checked rather than guessed.

What accuracy to expect

Accuracy depends on microphone placement and the acoustics of the room. In a normally noisy shop, service-counter conversations transcribe well enough for reliable analytics: trends, topics, tone and quotes. We continuously evaluate quality on real anonymised dialogues and tune the pipeline where the language mix is hardest.

Which languages are supported

Any major language. In practice, Estonian retail mostly means Estonian + Russian + English in one shop floor — exactly the combination VILFF is optimised and tested for daily.