Can an AI Voice Assistant Understand Accents? How to Test One
It depends on the system and the speaker, so the honest answer is to test it. Accents, regional words, unusual names, postcodes and poor phone lines all raise the chance of mishearing. Good design confirms key details back and offers a fallback or handover. This guide gives you a script to score a voice assistant with your real callers.
Why do accents cause errors for a voice assistant?
A voice assistant turns speech into text before it does anything else, and that first step is where most mishearing starts. Speech recognition systems learn from recorded examples. Speech that sounds very different from the examples a system has learned from may be recognised less reliably. We have not tested any system for this guide, and results differ between products and versions, so treat accent handling as something to check rather than assume.
It is also not only about accent in the narrow sense. Speed, volume, background noise, the quality of the phone line and whether the caller is using a speakerphone all play a part, and these combine with accent.
Which details are most likely to go wrong?
Names: surnames and place names that are not common in English, or that are spelt differently from how they sound.
Postcodes and addresses: a mix of letters and digits where similar sounds (B and D, M and N, F and S) are easy to confuse, especially on a compressed phone line.
Dialect and local words: regional terms for everyday things, or local place names pronounced in a way that does not match the spelling.
Numbers: phone numbers and reference numbers read quickly, in groups, or with 'double' and 'triple', or with 'oh' instead of 'zero'.
Dates and times: forms such as 'the third of the eleventh', 'half seven' or 'quarter to'.
Phone-line noise: wind, traffic, a workshop, a car, a busy kitchen or a weak mobile signal.
What does good design do about misheard details?
No speech recognition is perfect, so a well-built system is designed around the assumption that some words will be misheard. The aim is that a mistake is caught on the call, not discovered later.
Erudience designs, builds and runs voice systems, and read-back and handover are the behaviours we would look for in any set-up. None of them promises perfect recognition.
Confirms key details back. After taking a name, number, postcode or date, the assistant reads it back and asks the caller to confirm or correct it.
Offers a spell-out fallback. If a name or postcode does not land, it asks the caller to spell it, and may accept a phonetic alphabet such as 'B for Bravo' or 'B for Bertie'.
Limits the damage of one error by confirming before it books, sends a message or writes to a record.
Hands over cleanly. After a set number of failed attempts, or when the caller sounds frustrated, it offers a transfer, a callback or to take a message, rather than looping.
Uses known lists where possible, such as checking a postcode against a valid format, or matching a name against an existing customer record, to catch impossible results.
Logs the call and transcript so a person can review where it went wrong.
How to test a voice assistant with different accents
The most useful test uses the people who will actually call you. Build a short script, ask a range of people to read it, and score what the assistant understood. Keep it informal but consistent: the same script, the same scoring.
Decide in advance what counts as acceptable for your business. Missing a postcode and having it corrected on read-back is a very different result from silently booking the wrong address.
Choose a spread of speakers: colleagues, family, friends and, if you can ask, a few existing customers. Aim for varied regional accents and for speakers whose first language is not English. In the UK that range might include Scottish, Geordie, Welsh, Irish and Indian English speakers, among many others. These are examples of the spread to cover, not a ranking or a claim about how any system performs.
Give everyone the same script to read as if they were a caller. Include a full name with a less common surname, a postcode, a date and time for an appointment, a phone number, and a reference number of several digits.
Add a few questions in the speaker's own words: ask them to describe the reason for calling naturally, including any local terms they would normally use.
Record each call, with permission, and keep the transcript if the system provides one.
Score each item as understood first time, understood after a correction, or not understood. Also note whether the assistant read the detail back and whether the fallback worked.
Repeat a subset in noisy conditions: a car, a street, a room with a television on, a speakerphone, a weak mobile signal.
Look for patterns. If one type of detail, such as postcodes, fails for many speakers, that points to the design. If one speaker struggles across the board, note it and see whether the handover handled it well.
What to ask a provider about accents and noise
Which speech recognition is used, and can it be changed or tuned for my callers?
Can I add custom words, such as business names, product names, staff names and local place names?
How are names, postcodes and numbers confirmed on the call?
What is the fallback after a failed attempt, and how many attempts are allowed?
Can I see transcripts and recordings to review mistakes?
Can I run this test on a live line with my own callers before I commit?
How are mistakes fed back into improvements once the system is live?
Erudience services related to this guide
Use cases related to this guide
Terms used in this guide
More guides to read next
- How an AI Voice Assistant Answers a Phone Call, Step by Step
- What Can an AI Receptionist Do, and What Can't It?
- Questions to Ask Before You Buy an AI Phone Answering System
- Can an AI Voice Assistant Make Things Up? How to Keep It Honest
Frequently asked questions
Can an AI voice assistant understand regional UK accents?
It varies by system and by speaker, and we have not tested any system for this guide. The reliable way to find out is to have people with the accents your callers actually have read a test script, then score the results.
Why is a postcode harder than a normal sentence?
A postcode is a short string of letters and digits with no surrounding context to help. Similar-sounding letters are easy to confuse, particularly on a compressed phone line, so good set-ups read it back or ask for it to be spelt.
What should the assistant do if it keeps mishearing someone?
After a small number of attempts it should offer another route: spelling the detail, taking a message, arranging a callback or transferring to a person. It should not keep repeating the same question.
Does background noise matter as much as accent?
It can matter as much. Traffic, wind, a workshop or a poor mobile signal can make speech harder to recognise for any speaker, so include noisy tests in your script.
Is it fair to test with only a few people?
A small test will not give statistical proof, but it will show whether the design handles errors sensibly, which matters more. Use as wide a range of speakers as you can reach, and repeat the test after any changes.