Do AI Accent Changers Actually Work? What They Do and Don't
AI accent changers like Sanas and Krisp reshape accented English in real time. Here is what they actually do, where they stop, and when practice wins.
Direct answer
AI accent changers work for the job they were built for — making one live conversation easier to follow while the software is running — and not for the job most learners actually want, which is being understood when nothing is running at all. Tools like Sanas and Krisp reshape accented English in real time on a call. They do not teach you anything, and the moment you turn them off, your speech is exactly where it was before.
That is not a reason to avoid them. It is a reason to be clear about which problem you are solving: getting through a specific call, or getting better at speaking.
What does an AI accent changer actually do?
Real-time accent conversion takes your voice as you speak and edits it before it reaches the other person. The system finds sounds that listeners across accents tend to mishear and nudges them toward a more expected form, while trying to keep your pitch, timing, and tone recognisably yours.
The two best-known tools take different routes:
- Sanas converts the speaker’s accent at the source. It was built for call centres, after one of its founders experienced accent discrimination in a call-centre job, and it now runs in healthcare, logistics, and other phone-heavy industries. TechCrunch reported that Sanas raised a $65 million round in early 2025 at a valuation above $500 million, and that its models are trained on more than 50 million utterances of speech.
- Krisp added a listener-side option in March 2026. It adapts the incoming speech on the listener’s device and, by its own description, does not change how you sound to anyone else. Krisp describes it as running locally, at the phoneme level, with under 200 milliseconds of delay, and says it already processes more than 80 billion minutes of conversation a month across over 200 million devices.
Both are communication products. Neither is a course.
Where do they stop working?
The limit is structural, not a bug that a later version fixes.
| What you want | What an accent changer gives you |
|---|---|
| To be understood on today’s sales call | Yes, while it is switched on |
| To be understood in a shop, a hallway, an interview | No — the tool is not there |
| To stop a specific word being misheard | Only inside the app’s pipeline |
| To hear which sound made the word unclear | Nothing; it covers the problem instead of showing it |
| To sound like yourself | Partly; the more it changes, the less it is your voice |
An accent changer is a filter on the line. It is the audio version of a video call’s background blur: handy for the meeting, gone the moment you close the laptop, and no help at all when you are standing in the room.
The part worth thinking about
There is an open argument about whether accent conversion is a good idea at all. The engineers behind these tools built them from personal experience: Krisp’s co-founder Arto Minasyan told SiliconANGLE, “I know what it feels like to repeat yourself on a call, or to see someone concentrating on your pronunciation instead of your idea.” Sanas was started after one of its founders faced accent discrimination in a call-centre job.
But critics quoted in the same reporting point out that hearing a range of accents is itself what reduces bias, and that smoothing everyone toward one sound risks reinforcing the idea that some accents need fixing.
You do not have to settle that debate to use the tool sensibly. But “make my accent disappear” and “make my speech clear” are not the same goal, and only the second one is something you can take with you.
Is it cheating to use one?
If an accent changer gets you through a job you need to keep or a call that matters, that is a reasonable use of software. It just is not practice, because the change is made by the model, not by you. Nothing about your own speech is different afterwards.
The useful comparison is live captions or a translation app: scaffolding for a moment. They solve different problems: an accent changer buys clarity for one conversation, and learning the sounds gives you clarity you keep.
Do these tools send my voice somewhere?
It depends on the tool. Krisp says its listener-side feature runs on the listener’s own device with no cloud step; other services, including Sanas, process your speech through their own models. Check the specific product’s privacy documentation before using one on confidential calls.
This is also the clearest line between an accent changer and what Phonema does. Phonema never touches how you sound to another person. It listens to a phrase on your iPhone, scores each of the 42 English sounds on its own, and tells you which word was unclear and why — and the audio does not leave the device to do it.
If your goal is to be understood without the tool
Work on the small number of sounds that carry most of the misunderstanding — the same ones that trip speech recognition:
- The /θ/ in think, often heard as sink or tink.
- Final consonants — the /t/ in want, the /d/ in called — which many accents soften and which listeners lean on.
- Short /ɪ/ in ship vs. long /iː/ in sheep: a small length difference doing a lot of work.
- The English /ɹ/, which is a different sound from a Spanish or French R.
Practise them inside phrases you actually say, record yourself, and check one thing per attempt: did the key word land? This is slower than flipping a switch. It is also the version that is still true tomorrow.
Bottom line
An AI accent changer is a real tool for a narrow problem: one live conversation, right now, with the software running. It does not build a skill, it can cover the specific sound you would need to work on, and the debate about whether it should exist at all is not settled. If what you want is to be understood in the room, with the laptop closed, that is a different project — and it starts with knowing which sound is costing you the word.