How accurate is a Kannada voice bot on real phone calls?
No honest single figure exists, and any vendor quoting one percentage for Kannada should show how it was measured. Accuracy on a real call depends on the line, the speaker, the region and what is being captured. Names, numbers and Kanglish are hardest. Outpero publishes no accuracy percentage, so measure it on a sample of your own recorded calls.
Three kinds of accuracy
- 01Hearing: did the transcript contain the words the caller said? This is what word error rate measures.
- 02Understanding: did the agent grasp the meaning, such as a request to move a visit to the evening?
- 03Capturing: did the saved fields, such as name, date and amount, match what was said?
A call can score well on the first and still fail the third. If the agent hears 'hadinaidu saavira' and stores fifty thousand, the transcript looks fine and the record is wrong.
What lowers accuracy on Kannada calls
- —Verb endings and short particles carry the meaning, so a clipped syllable on a weak signal can turn a question into a statement.
- —Spoken Kannada differs from the written form, and speech varies between Mysuru, Hubballi and Mangaluru.
- —Numbers such as 15 and 50, or 20 and 30, can sound close over a crackling line.
- —Kanglish moves in and out of English quickly, often on the very words that matter, such as product names and amounts.
- —Surnames, village names and addresses are the least predictable words on any call.
How to measure it on your own calls
- 01Collect 50 recordings from real or realistic callers, across regions and including some from noisy places.
- 02Listen to each and write down the facts you needed: name, area, time, amount, intent.
- 03Compare them with the transcript and the captured fields from the call log.
- 04Count failures by type, for example numbers, names, intent and Kanglish, so the fixes are targeted.
- 05Repeat after changing the script, and compare the same type of failure again.
Ways to reduce errors
Short closed questions, read-backs of dates and amounts, and a confirmation by WhatsApp message where that action is set up all help. Outpero records every call and returns a transcript, summary and captured fields, so each error can be traced and the script tuned. Where a detail is critical, such as an EMI amount, ask the agent to confirm it aloud before it is saved.
Want to hear an AI voice agent handle this on a real call?
Follow-up questions
Is a Kannada voice bot as accurate as an English one?
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It cannot be assumed. English has had more speech data and tooling, and Kannada adds regional variation and Kanglish. Some vendors perform well in both, others only in English. The only reliable comparison is the same test, run with the same callers, in both languages.
What should I do when the transcript is wrong?
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Listen to the recording first, because the transcript may be the weak link rather than the conversation. Then note the type of error, adjust the script to avoid the hard word, and add a read-back step. Repeat the check on a fresh batch of calls.