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Remote hiring and the voice on the call.

Candidate impersonation in remote interviews is a real and growing problem, and voice detection is a surprisingly small part of the answer. Interview audio is heavily processed by the conferencing platform before it ever reaches you, the accusation risk is severe, and the controls that actually work are procedural rather than technical. Here is an honest account of what to do.

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Reality check

Why the detector is the weakest part of your defence.

Three structural problems, none of which is about detection quality.

  1. Conferencing audio is heavily processed. Noise suppression, automatic gain control and aggressive codecs are doing a great deal to the signal before you ever see a file. That processing removes the same irregularities detection depends on, which compresses scores toward the middle for everyone — genuine candidates included.
  2. The error that matters lands on a real person. A missed impostor costs you a bad hire you will discover. A wrongly flagged candidate is a person who loses a job over something they cannot disprove, and who may have a discrimination claim if the flagging correlates with accent, equipment quality or a speech difference. That asymmetry should govern your whole process.
  3. Detection is retrospective. It runs on a recording afterwards. It does not tell you during the call, which is when you could actually do something.
Never reject a candidate on a detector score. It is not forensic-grade and must never be the sole basis for an employment decision. If a result concerns you, the correct next step is a further live conversation — not a rejection, and not an accusation.
Controls

What actually works instead.

All of these are cheap, none of them depends on a tool, and they apply equally to every candidate.

Live, unscripted conversation

The strongest control there is. Ask follow-up questions that depend on the previous answer, interrupt gently, change direction mid-topic. Real-time voice systems and coached impostors both degrade under genuine conversational turn-taking in a way that is obvious to a human listener.

Ask about specifics only the real candidate would know

Not credentials — the detail of the work. Why that architecture rather than the obvious alternative, what went wrong on the project, who disagreed with them. Someone relaying answers from elsewhere cannot keep up with a genuine technical follow-up.

Camera on, and consistent

Apply it as a stated policy for all candidates at a defined stage, not selectively when someone raises your suspicion. Selective application is where discrimination risk enters.

Identity verification at the right point

Formal identity checks belong in your onboarding process where they can be applied uniformly and lawfully, not improvised mid-interview because a voice sounded odd.

Structure the process, not the tooling

A live technical exercise, a scheduled call at a fixed time, and consistent interviewers across a panel do more against impersonation than any audio analysis. They also improve hiring quality generally, which is a better reason to adopt them.

Where a check does help: reviewing a recorded screening call after other signals have already raised a question, as one input into whether to run another live round. That is a legitimate, proportionate use. Making it a routine screen on every candidate is neither.
If you do check

Doing it fairly, if you do it at all.

If your process includes checking recorded interview audio, a few things keep it defensible.

  • Tell candidates. Recording and analysing interview audio has data-protection implications in most jurisdictions, and doing it covertly is the version that creates liability. Notice and a lawful basis are for your own counsel to confirm, not for a guide to assert.
  • Apply it uniformly. Every candidate at a defined stage, or none. Ad-hoc checks triggered by an interviewer's hunch are exactly where bias enters.
  • Use a control. Another recording of the same candidate from the same platform gives you a baseline. The comparison method matters more here than almost anywhere, because platform processing dominates isolated scores.
  • Write down the limits with the result. If the note in your ATS says only “flagged as AI”, it will be read as fact by whoever sees it next. Record the audio conditions and the caveat alongside it.
  • Give the candidate a route to respond. A process with no way to contest a flag is not a process. A short live call resolves nearly every genuine case.
Not forensic-grade. A TextSight voice result is a triage signal, not proof, and it must never be the sole basis for a disciplinary, employment, financial or legal decision. Our full position on what a result is worth is here.
FAQ

Hiring team questions.

Can I reject a candidate because a voice detector flagged their interview?
No. It is not forensic-grade analysis and must never be the sole basis for an employment decision. Beyond the fairness problem, a rejection resting on an unexplainable score is difficult to defend if challenged. If a result concerns you, run another live conversation.
Why do genuine candidates get flagged?
Conferencing platforms apply noise suppression and automatic gain control that strip out the irregularities detection relies on, which pushes everyone's scores toward the middle. Short clips, heavy accents captured through aggressive processing, low-quality microphones and quiet rooms all add noise to the result. The error lands on a real person, which is why it should never decide anything alone.
What actually stops candidate impersonation?
Live unscripted conversation with genuine follow-up questions, specific technical probing on the candidate's own claimed work, a consistent camera policy applied to everyone at a defined stage, and formal identity verification in onboarding where it can be applied uniformly. Procedural controls beat audio analysis substantially here.
Do I have to tell candidates I am analysing their audio?
Recording and analysing interview audio carries data-protection obligations in most jurisdictions and covert analysis is the version that creates liability. Notice and a lawful basis are questions for your own legal counsel — but as a matter of practice, telling candidates costs nothing and removes most of the risk.
Can I check a live interview in real time?
No. Detection runs on a recorded file afterwards, not on a live stream. During the interview, unscripted conversation is what works.
Is this useful for high-volume screening?
We would advise against it as a routine screen. The false-positive burden falls on genuine applicants, platform processing makes scores unreliable at exactly the audio quality screening produces, and a systematic flagging process that correlates with accent or equipment quality carries real discrimination risk. Reviewing a specific call after other signals raised a question is the proportionate use.
Related

More voice detection guides.

How accurate is it, really?

Why we publish no single accuracy percentage, what false positives look like, and how to weigh a result.

See our position →

Compare two clips

The control-recording method: run a known-genuine clip alongside the suspect one and read the gap.

Learn the method →

Choosing a detector

The questions to ask any vendor, the claims to distrust, and how to run your own test.

Read the buyer's guide →

Have a recorded screening call? Treat it as one signal.

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Never a sole basis for a hiring decision · false positives land on real candidates