One detector, many decisions.

AI voice detection tells you how likely it is that a recorded voice was machine-generated. Fraud teams use it on calls that ask for money or codes, and contact centres use it to screen recorded calls at volume. Newsrooms check clips before they publish, investigators document evidence, and developers build it into products through an API. Every check returns a verdict on a four-step scale and an AI probability score, with a score for each segment on longer clips.

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By the AI Voice Detector Editorial Team · Sources checked October 2026

One verdict
AI score94%
VerdictAI Generated
Segments5 of 6 flagged
Different decisions
The same result drives a different action for each team.

What does an AI voice verdict actually tell you?

Every result has three parts, whoever is reading it. The free check and the API use the same model, so the result means the same thing in both. It takes about a minute to learn to read one.

Verdict · voicemail_0412.m4a38 s · mono
1 AI probability score94%
0% human100% AI
2 VerdictAI Generated
3 Segments5 of 6 flagged
An example verdict, annotated. Sample values.
  1. 1
    AI score. How likely it is that the voice was machine-generated, from 0 to 100%. It is a likelihood, not a yes or no.
  2. 2
    Verdict. The score placed on a four-step scale: AI Generated (86% and above), Likely AI (50 to 85%), Likely Human (16 to 49%) and Human (below 16%). The two middle steps mean the call is not decisive.
  3. 3
    Segments. On longer clips, a score for each part of the recording, so you can see where it sounds synthetic. It does not say which tool made the voice.
InRecordingVoicemail, call recording, voice note, clip
AnalyzeDetectorFree check or REST API
OutVerdictVerdict, AI score, segments
AI Generated, clean clipAct and documentStop the payment, hold the clip or add the finding to the case file.
Likely AI, Likely Human, or a quality warningGet a better copyAsk for the original file or a longer sample. Do not re-record it on another device.
Human, clean clipProbably humanCarry on with your normal checks. A real person can still be lying.

How a recording becomes a decision. You choose what each verdict triggers.

Three ways to misread a verdict

"A low score means the call is safe."

It means the voice is probably human. The person could still be lying, so the request goes through your normal checks.

"A high score settles it."

Only on a clean clip. A high score on a two-second clip does not prove much, and the app warns you when a clip is under three seconds or recorded at low quality.

"The detector tells me who is speaking."

It tells you whether a voice is synthetic, not whose voice it is.

The detector accepts MP3, WAV, M4A, OGG, FLAC and AAC. Longer, cleaner audio gives better results, and a borderline score lands in Likely AI or Likely Human rather than a firm call. Guides for specific voice tools live on the detect a voice pages, and the method is explained in how to detect AI voices.

Which use case is yours?

Six teams read the same result and act differently. Pick yours to jump to how they work.

Fraud teams
For fraud analysts at banks and insurers

Is this caller really who they say they are?

Contact centres
For QA and risk leads reviewing recorded calls

Which recorded calls need a human to listen?

Newsrooms
For editors and fact-checkers on deadline

Can we run this clip?

Legal and investigations
For counsel and investigators building a case file

Can we show how we tested this recording?

Music and audio
For labels, platforms and producers

Was this track made with an AI music tool?

Developers
For platform and product teams

Should we build detection or buy it?

Compare all six side by side
Each use case compared by decision, result and limit
You areThe decision you faceWhat the verdict gives youWhat it cannot do
Fraud teamsBanks, insurers and KYCIs this caller really who they say they are?A written reason to stop the payment or escalateWorks on recordings, not live calls. Does not identify the speaker.
Contact centresQA and risk leadsWhich recorded calls need a human to listen?A ranked review queue from thousands of recordingsChecks the voice, not what was said. API on paid plans.
NewsroomsEditors and fact-checkersCan we run this clip?A documented check to support the call either wayDoes not verify the story or the source.
Legal and investigationsCounsel and investigatorsCan we show how we tested this recording?A test result an expert can repeatDoes not decide admissibility.
DevelopersPlatform and product teamsShould we build detection or buy it?The same verdict, returned as JSONWorks on files, not live streams. Paid plans only.
Music and audioLabels, platforms and producersWas this track made with an AI music tool?A check built for songs, not speechUse the AI music detector, not the voice check.

Swipe sideways to see every column

How do fraud teams use AI voice detection?

A recorded voice asks for money, a one-time passcode or an account change, and an analyst has to decide whether to act. Tools such as ElevenLabs and Resemble can clone a voice from a short sample, so the caller can sound exactly like a customer, an executive or a colleague.

voicemail_0412.m4a · 38 sFlagged
Voicemail waveform, 38 secondsFrom 0:21 to 0:30, highlighted, the caller asks the listener to read out the code just sent.
0:000:100:200:300:38
0:02 · Pretext"This is the fraud team at your bank."
0:11 · Urgency"We have blocked a 900 dollar charge."
0:21 · The ask"Read me the code we just sent."
Verdict94% · AI Generated
Anatomy of a cloned-voice voicemail. Sample values. Script modelled on the bank fraud alert pretext in vishing vs smishing.
22,364

Complaints involving AI reported to the FBI in 2025, with about 893 million dollars lost. Voice cloning was named in business email compromise and family emergency scams.

FBI IC3 2025 report
3.5 billion

Dollars reported lost to imposter scams across every channel in 2025.

FTC, June 2026

Recordings worth screening

  1. A voicemail or call recording that asks someone to read out a one-time passcode. No legitimate caller needs it (FTC, March 2024).
  2. An executive's voice instructing an urgent wire or a change of bank details.
  3. A help desk call asking for a password or MFA reset. The FBI and CISA describe Scattered Spider using this pretext (CISA AA23-320A). MITRE lists it as voice spearphishing (ATT&CK T1566.004).
  4. Insurance. A recorded statement in a claim, where the voice is the main evidence.
  5. KYC. A voice sample submitted during onboarding or account recovery, where a cloned voice could pass as the applicant.
What the verdict changes

An AI Generated verdict on a clean recording backs up a hunch with evidence. The analyst can stop the payment, escalate and attach the verdict to the file.

The limit

The detector works on recordings, not live calls, and it does not identify the speaker. A low score does not make a request safe. Use it alongside callbacks and dual approval, not instead of them.

Where does detection sit next to your other controls?

Each control answers a different question, and only detection looks at the audio itself. They work best together.

Fraud controls compared
ControlWhat it answersBlind spotFlags a cloned voice on a recording?
AI voice detectionIs this recorded voice machine-generated?Who is speaking, or whether the request is genuine.Yes
Voice biometricsDoes this voice match an enrolled customer?A good clone of the customer's voice may still pass.Not by design
Caller ID with STIR/SHAKENWas the number attested on participating networks? (FCC)Who is speaking. Caller ID spoofing is common (FCC).No
Callback to a known numberDoes the real person confirm the request?Nothing about a recording you already have.Indirectly
One-time passcodeDoes the person signing in hold the device?Whether someone talked them into reading the code aloud.No

Swipe sideways to see every column

Fraud detection use case What is vishing?Vishing examples

How do call centres detect AI voice fraud in recorded calls?

A contact centre records thousands of calls a day. A QA or risk lead cannot listen to all of them, and a cloned voice on a call to reset an account or move money sounds like any other customer. The job is to find the few recordings a person should hear.

Send stored recordings to the REST API from your own job. Each call comes back with a verdict, an AI score and per-segment scores, so the review team starts with the calls that score high and moves on.

Review queue · overnight run
Sample review queue from an overnight run of recorded calls
RecordingAI scoreVerdictNext step
call_0193.wavAccount reset91%AI GeneratedSend to review
call_0195.wavPayment change58%Likely AIRe-check a cleaner copy
call_0196.wavBalance query12%HumanNormal checks
call_0194.wavAddress update7%HumanNormal checks
Recordings sorted by verdict so reviewers hear the riskiest calls first. Sample values.
  1. 01Export recordingsPull stored call recordings from your call recording or QA platform.
  2. 02Check each fileUpload each recording, then request a detection. The verdict comes back in the same call.
  3. 03Review what scores highRoute AI Generated calls to a reviewer. Re-check Likely AI calls with a cleaner copy.
What the verdict changes

Reviewers spend their time on the handful of calls most likely to involve a synthetic voice, with a verdict attached to each one.

The limit

The detector checks whether the voice is machine-generated. It does not transcribe calls or search them for what was said, so it will not flag fraud mentioned in a call by a real person. It works on recordings, not live calls, and API access is on the paid plans.

Developer API See plansFraud detection use case

How do newsrooms verify audio before publishing?

An editor has a leaked clip of a public figure and has to decide whether to run it. Public figures have hours of speeches online, which is more than enough to clone their voice.

Regulators take this seriously. In February 2024 the FCC ruled that AI-generated voices in robocalls count as artificial voices under the Telephone Consumer Protection Act (FCC, 8 February 2024). So those calls need the same consent as any prerecorded call.

Desk review · leaked_clip.m4a0:41
Clip waveform, 41 secondsA re-shared clip under desk review.
AI score71%
VerdictLikely AI
Next stepAsk for the original
A re-shared clip lands in Likely AI: not decisive. Sample values.

A pre-publication audio check

Six steps · three stages

Secure the file

  1. 01Get the original file from the source, not a screen recording or a re-share.

Test the voice

  1. 02Run it through the detector and note the verdict, the AI score and which segments score high.
  2. 03If the verdict is borderline or the app warns about the clip, get a longer or cleaner copy before you draw any conclusion.

Report it out

  1. 04Check provenance. Look for C2PA Content Credentials where the publishing tool supports them.
  2. 05Check what the clip says against independent sources, as you would any claim.
  3. 06Write down what you checked and when, so the desk can explain its decision later.
What the verdict changes

The desk gets a documented reason to hold the clip, or one more piece of support for running it. Either way, the decision is on the record.

The limit

A verdict does not verify the story. It only tells you whether the voice shows signs of being generated. The full method is in how to verify AI audio.

Newsrooms use case

How do developers add AI voice detection to a product?

You can train and maintain your own detector, or call ours. The REST API returns the same verdict as the free check in JSON, so your product can act on it automatically. API access is on Starter and above.

  1. 01 · Send a recording
    POST /api/v1/uploads/voice
PUT  {signed upload URL}
POST /api/v1/detect/voice
  2. 02 · Receive the verdict
    {
  "verdict": "likely_ai",
  "ai_score_percent": 83,
  "segment_count": 4
}
  3. 03 · Act on your threshold
    if (r.ai_score_percent >= threshold) {
  routeToReview(file)
}

Common integration patterns

Overnight screening
Check stored call recordings from a scheduled job and send flagged files to a review queue.
Upload checks
Check voice notes or audio posts as users upload them to your platform.
Case tools
Add a button to a case management tool that attaches a verdict to the record.
Contracts and volume
Over 20,000 detections a month, or need invoicing? Contact sales.
The limit

The API analyzes files, not live audio streams. You set the threshold, based on what a false alarm costs you. Plans and volumes are on the pricing page.

Read the API docsContact sales

How do you check whether a song was made with AI?

Songs are not voicemails. A track carries instruments, effects and mixed vocals, so the question is whether the music was produced with a tool such as Suno, not whether a caller is real.

For that, use the AI music detector. It is the check built for songs. The Suno guide covers one of the most common generators.

Open the AI music detectorSuno guide
track_master.wav · 3:12Song
Song waveform, 3 minutes 12 secondsA full song, denser and louder than a voice recording.
Music needs its own check. The voice detector is tuned for speech.

Frequently asked questions

What is AI voice detection used for?

It helps people decide whether a recorded voice is human or machine-generated before they act on it. Fraud teams use it on calls that request money or codes. Contact centres use it to screen recorded calls at volume. Newsrooms use it before publishing audio. Investigators use it to document evidence. Developers build it into their own products through an API.

Does the detector monitor live phone calls?

No. It analyzes recordings that already exist, such as a saved voicemail, a call recording, a voice note or an uploaded clip. It does not intercept, monitor or block live calls. Teams that need screening at volume send recordings to the REST API from their own call recording or case tools.

Can a contact centre screen recorded calls automatically?

Yes, through the REST API on the paid plans. Your system sends each stored call recording to the API and receives a verdict for each one in the same call. The detector checks whether the voice is machine-generated. It does not transcribe calls or search them for what was said.

What does a verdict include?

Three things: an AI probability score from 0 to 100%, a verdict on a four-step scale from Human to AI Generated, and on longer clips a score for each segment. Read them together. A high score on a short or compressed clip is not a strong result.

Can I check a recording for free?

Yes. The public detector at aivoicedetector.com/is-this-ai checks a single recording for free with no account. Upload a voicemail, a call recording or a voice note and read the verdict on screen. API access and higher volumes start on the paid plans, which are listed with their prices on the pricing page.

Is an AI voice verdict proof in court?

Not on its own. Under US Federal Rule of Evidence 901, the party offering a recording must show it is what they claim it is. A documented detector verdict can be one part of that showing. Whether it is admitted, and how much weight it carries, is for counsel and the court.

Why would a verdict come back borderline?

A Likely AI or Likely Human verdict usually means the clip gave the model too little to work with. Very short clips, heavy compression from phone networks or messaging apps, a recording replayed through a speaker, and music or overlapping voices all make results less reliable. Ask for the original file, avoid re-recording it on another device, and run the clearest copy you have.

Have a recording you are not sure about?

Check it free, no account needed. Screening at volume or need a contract? Talk to sales.

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