Can AI transcribe conversations where the customer and the clerk speak different languages?

Yes. Modern speech recognition handles dialogues where the customer and the clerk speak different languages - or switch languages mid-conversation. VILFF was built for exactly this environment: it transcribes dozens of languages, separates who said what, and shows the transcript in the portal with a translation into the language you prefer.

Why mixed-language dialogues are hard

Classic speech-to-text expects one language per recording. Real shop-floor speech is different: a customer asks in one language, the clerk answers in another, product and brand names come in English, and single sentences mix all of it at once. That is how people speak in border regions, in cities with a large migrant population, in tourist areas and anywhere staff and customers have different native languages. Add background noise, distance from the microphone and accents, and most general-purpose tools break.

How VILFF handles it

• Speaker separation - every utterance is attributed to the customer or the employee;
• Language at utterance level - 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, with the original preserved;
• Noise-tolerant pipeline - a speech detector cuts silence and distant conversations, and low-confidence segments are re-checked rather than guessed.

What accuracy to expect

Accuracy depends on microphone placement and room acoustics. In a normally noisy store, 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

All major languages. In practice one shop floor usually carries two or three: the country's official language, the language of a large local community, and English - exactly the combination VILFF is optimised for and tested on daily. If you have a rare language pair, send us a sample recording and we will check transcription quality before you start.