Free AI Voice & Audio Detector
Upload MP3, WAV, M4A, OGG, FLAC, or WebM/Opus audio, or record a sample from your microphone, to check AI voices, voice clones, AI-generated sound, and deepfake audio with a private browser-side scan. No signup, email, or server upload required.
AI voice and sound detector for voice clones, deepfake audio, and scam-call triage
Upload a voice clip, narrated audio, AI music sample, or suspicious sound file to check browser-readable signals such as bitrate, silence, clipping, dynamic range, zero-crossing, and micro-variation. The file stays in your browser, making EyeSift a free no-signup first pass before you verify the speaker or source through a separate trusted channel.
Recording and samples stay in your browser and are analyzed locally via Web Audio API. Nothing is sent to a server.
How the AI Voice Detector Works
EyeSift decodes the selected audio locally when your browser supports the format, then checks duration, bitrate, waveform energy, silence ratio, clipping, dynamic range, zero-crossing variation, and micro-variation. Use this free AI voice detector as a first-pass synthetic-voice and AI-generated sound screen, not as forensic proof. It does not decode SynthID watermarks or cryptographically verify C2PA manifests, so high-stakes review should also use the supported provider verifier, original file history, and source context.
AI Voice vs AI Sound Detection
| Search intent | Use EyeSift for | Important limit |
|---|---|---|
| AI voice detector | Speech, voice notes, narrated clips, voice-clone checks, and scam-call triage. | The score is a screening signal and must be verified with speaker/source context. |
| AI sound detector | AI-generated sound, music, podcast, audiobook, or sound-effect clips when you need synthetic-audio triage. | EyeSift does not identify the object or scene that made a sound. It checks audio quality and waveform-risk signals. |
| Watermark or provenance check | A first pass before checking provider-specific watermarks, C2PA credentials, source history, or original files. | Missing watermarks or credentials are not proof that audio is human-recorded. |
Voice Clone Review Checklist
| Check | Why it matters | Best next action |
|---|---|---|
| Original file | Messenger downloads, screen recordings, and reposts hide useful artifacts. | Use the earliest available WAV, FLAC, M4A, or high-quality MP3. |
| Known speaker sample | A believable clone can sound natural without matching the real speaker perfectly. | Compare cadence, breathing, pauses, and repeated phrases against a trusted sample. |
| Provenance | C2PA credentials and platform watermarks such as SynthID can preserve origin signals when supported. | Check provider verification surfaces and the original file before relying on waveform clues. |
| Context | FTC guidance treats voice cloning as a deception risk, especially for scams and impersonation. | Verify the source through a separate channel before acting on urgent requests. |
Sources Checked for Voice-Clone Risk
Reviewed August 11, 2026. These sources support the page's practical guidance: use the detector as triage, then verify urgent money, account, identity, source, or safety requests through a separate trusted channel. Provider-specific watermark checks and C2PA provenance can add evidence when supported, but missing signals are not proof that audio is human-recorded.
What We Screen For
- Very smooth waveform transitions that can appear in synthetic or heavily processed voices
- Low dynamic variation, silence-heavy clips, hard limiting, clipping, or bitrate limits that reduce confidence
- Voice cloning, text-to-speech, and AI-generated audio risk signals for manual review
- Format and quality limits that can make a result inconclusive
Supported Audio Formats
WAV, FLAC
Raw or lossless files preserve waveform detail.
M4A, MP3, OGG
Useful for screening when bitrate is high enough.
Voice-note exports, reposts
Heavy compression can hide or create artifacts.
Voice Detection Guides
Audio and Music Provenance
Related Tools
Which AI voice generators does this screen for?
EyeSift is generator-agnostic. It does not look for a vendor watermark or a specific model fingerprint; it screens the waveform and container for general smoothness, dynamics, silence, and quality patterns that can appear in synthetic or heavily processed speech, whichever system produced it. That means it can be used as a first pass on audio from ElevenLabs, OpenAI text-to-speech, Google Cloud and Azure TTS, Amazon Polly, PlayHT, Murf, Resemble, Speechify, and voice-clone apps, and on AI-generated music from Suno or Udio. It also means it cannot tell you which generator produced a clip.
When you need vendor attribution, pair this check with the vendor's own classifier: the ElevenLabs AI Speech Classifier reports the probability that audio was generated with ElevenLabs specifically (first minute only, no login). It is not a general-purpose detector for other vendors' output, and ElevenLabs notes it does not reliably classify audio from its Eleven v3 model.
How this compares with other AI voice detectors
| Detector type | Where your audio goes | Scope | Best for |
|---|---|---|---|
| EyeSift (this page) | Stays in your browser; no upload, no account | Generator-agnostic screening of speech, voice notes, narration, and AI music; no vendor attribution | Fast private first pass before you decide whether to escalate |
| Vendor classifiers (e.g. ElevenLabs) | Uploaded to the vendor | Only that vendor's own output, typically the first minute of a file | Confirming or ruling out one specific generator |
| Free web checkers with server models | Uploaded to the service | Percentage verdicts from a hosted model; daily limits or logins are common | A second opinion when privacy is not a concern |
| Enterprise deepfake detection (Pindrop, Resemble Detect, Hiya, Reality Defender) | Processed on their infrastructure under contract | Live-call and batch detection; accuracy figures are vendor-reported under their own test conditions | Call centers, fraud teams, and platforms that need audited results |
Research challenges such as ASVspoof have found that detectors often lose accuracy on compressed or phone-transmitted audio, so treat any single score, including this one, as a screening signal rather than proof.
How to tell if a voice is AI: 8 manual checks
A detector score is one input. Before you act on it, listen to the clip with these eight checks in mind. The third column is honest about what EyeSift's browser-side measurements can and cannot flag: the tool reads level, silence, clipping, crest factor, zero-crossing, and micro-variation from the decoded waveform, so anything that lives in pitch, pronunciation, or scene context is yours to judge. The full walkthrough with examples is in our guide on how to tell if a voice is AI-generated.
| Check | What to listen for | Can EyeSift flag it? |
|---|---|---|
| 1. Breaths and pauses | Real speakers inhale before long phrases and pause unevenly. Synthetic narration often has no audible breaths, or breaths placed at grammatically neat but physically odd points. | Partly. The silence ratio and micro-variation metrics can hint at unusually clean gaps, but EyeSift does not detect breaths as events. |
| 2. Prosody and intonation | Pitch that rises and falls with meaning, questions that actually lift at the end, emphasis on the word that matters. Clones can sound fluent yet emotionally flat or oddly sing-song. | No. Pitch and intonation are spectral properties; EyeSift only measures level and waveform variation. |
| 3. Room tone and reverb | A real room leaves a consistent noise floor and reflections behind the voice. A generated voice is often “too dry” or carries reverb that changes between sentences. | Indirectly. A very low noise floor shows up as a high silence ratio and low RMS between phrases, which the tool reports without interpreting it as room tone. |
| 4. Plosives and sibilance | P, B, T and K sounds that pop unevenly, S sounds that vary in brightness. Generated speech can render them identically every time or smooth them away entirely. | Partly. Clipping and crest-factor checks catch harsh peaks, but EyeSift cannot tell a plosive from any other transient. |
| 5. Background consistency | Traffic, air conditioning, or a TV in the background should continue through the whole clip. A clone pasted over a scene often has background that cuts, loops, or disappears when the voice starts. | No. EyeSift does not separate the voice from the background; listen for this yourself. |
| 6. Unnatural word stress | Names, acronyms, numbers, and place names stressed on the wrong syllable, or read with the pronunciation of a different accent from the rest of the sentence. | No. Stress and pronunciation are linguistic, not measurable from level data. |
| 7. Repeated micro-patterns | If a word or phrase occurs twice, compare the two renderings. Humans never say a phrase identically; text-to-speech often produces near-identical waveforms. | Partly. Very low micro-variation and zero-crossing variation across a long clip are the closest waveform signal, but EyeSift does not align repeated phrases. |
| 8. Metadata and provenance | Where did the file first appear, is it the original export or a messenger re-encode, does it carry a C2PA credential or a vendor watermark that a supported verifier can read? | Partly. EyeSift reports container facts such as bitrate and sample rate, but it does not decode SynthID or ElevenLabs watermarks and does not cryptographically verify C2PA manifests. |
What EyeSift can flag
- Unusually smooth waveform transitions and low micro-variation over long clips
- Flattened dynamics, hard limiting, and clipping that suggest heavy processing
- Silence-heavy, very short, or very low-bitrate files that cannot support a confident call
- Container facts such as sample rate, channels, and estimated bitrate for your notes
What EyeSift cannot flag
- Which generator made a clip, or whether it came from ElevenLabs, OpenAI, or Google
- Vendor watermarks such as SynthID or the ElevenLabs mark; it has no decoder
- Cryptographic validity of a C2PA manifest, only the presence of container markers
- Pitch, accent, pronunciation, or whether the speaker is who they claim to be
If the clip is a call or voice note asking for money, credentials, or urgent action, skip straight to our caller verification steps from FTC and FBI guidance and confirm the person on a number you already trust before anything else.
Vendor detectors and provenance: what exists in 2026
Beyond generic screening, three kinds of stronger evidence exist: vendor classifiers that recognise their own generator, inaudible watermarks that a supported verifier can read, and signed C2PA provenance. Each answers a narrow question, and none of them proves a voice is human when the signal is absent. The rows below were checked against the vendors' own pages on September 17, 2026; accuracy figures are the vendors' claims, not independent results. For the deeper explanation see does ElevenLabs watermark its audio? and our honest comparison of free AI voice detectors.
| Detector or standard | Scope and limits | Access | Verification note |
|---|---|---|---|
| ElevenLabs AI Speech Classifier | Detects speech generated with ElevenLabs only. ElevenLabs says it reliably identifies most of its models but does not reliably classify Eleven v3 audio and cannot detect other providers. | Free, no login, first minute of a common audio or video file is analyzed. | Checked on elevenlabs.io on September 17, 2026. |
| ElevenLabs audio watermark | ElevenLabs says it embeds imperceptible watermarks in audio it generates so origin can be verified; its help center references SynthID. Whether the mark survives editing, or covers third-party models served through ElevenLabs, is not stated. | Verification is through ElevenLabs’ own tools; there is no public decoder for other sites. | Help-center wording checked September 17, 2026; persistence claims unverified. |
| Google SynthID for audio | Watermark embedded in audio from supported Google systems, currently Lyria music and NotebookLM audio. Google says it is inaudible and survives noise, MP3 compression, and speed changes. It says nothing about voices made elsewhere. | Ask the Gemini app whether a clip carries a SynthID watermark; the SynthID Detector portal, which pinpoints watermarked audio segments, is still limited to early testers via waitlist. | Checked on deepmind.google and blog.google on September 17, 2026. |
| C2PA audio provenance | Signed provenance metadata, not a watermark. The C2PA 2.1 specification lists RIFF (WAV), ID3 (MP3), and AIFF containers, so audio can carry Content Credentials when the producing tool signs them. | Credentials are read by verifier tools; re-encoding or messenger export usually strips them. Missing credentials are not evidence of a human voice. | Container list checked in the C2PA 2.1 specification on September 17, 2026. |
| Resemble Detect | Cross-generator deepfake detection for audio, video, and images, including real-time analysis in meeting platforms and batch checks. Accuracy figures on its site (up to 99.5 percent) are vendor-reported. | First detection free, then paid plans and an API. | Product claims checked on resemble.ai on September 17, 2026; accuracy not independently verified here. |
| Pindrop Pulse | Live deepfake and liveness detection for contact centers and video meetings. Pindrop reports 99 percent detection on known engines, over 90 percent on unseen engines, and under 1 percent false positives, all self-reported. | Enterprise only; demo request, no free tier. | Product claims checked on pindrop.com on September 17, 2026; accuracy not independently verified here. |
Where EyeSift fits: run it first because it is free, private, and instant; then use the vendor classifier if you suspect a specific generator, check provenance where the file supports it, and verify the speaker through a known channel. Teachers, podcasters, and hiring teams can follow the step-by-step version in AI voice detection for teachers, podcasters and HR.
How to Tell If a Voice Is AI-Generated
Eight listening checks, what heuristics can and cannot catch, and when to escalate.
Verify a Caller: FTC and FBI Guidance
Call back on a known number, family code words, and what to do if money was sent.
Free AI Voice Detectors 2026
What each free tier actually includes: signup, upload, clip limits, and generator scope.
Does ElevenLabs Watermark Its Audio?
Watermarks, SynthID, C2PA, and classifiers explained without overclaiming.
Frequently Asked Questions
Can I record my voice instead of uploading a file?
Yes. Use the microphone button under the upload box to record up to 30 seconds. The recording is captured with your browser's MediaRecorder, kept on your device, and analyzed exactly like an uploaded file.
Does it detect ElevenLabs, OpenAI, or PlayHT voices specifically?
It applies the same generator-agnostic waveform checks to audio from any of them, but it is not tuned to a specific vendor, can miss high-quality synthetic voices, and does not attribute a clip to one vendor. For vendor attribution use that vendor's classifier, such as the ElevenLabs AI Speech Classifier, alongside this check.
Does it work on WhatsApp voice notes or phone call recordings?
It can decode WebM, Opus, OGG, M4A, and MP3 voice notes, but heavy compression removes detail and lowers reliability. Export the original file where possible, avoid re-recording from a speaker, and treat low-bitrate results as weak evidence.
What is an AI voice detector?
An AI voice detector is a screening tool that checks a voice recording for signals associated with synthetic speech, voice cloning, text-to-speech, or deepfake audio. EyeSift runs this check in your browser and reports a triage score, not forensic proof.
Is EyeSift a free AI voice detector?
Yes. EyeSift is a free AI voice detector for browser-side triage. It screens MP3, WAV, M4A, OGG, and FLAC files for synthetic-voice, voice-clone, and deepfake-audio risk signals without signup, email, or server upload. Results are review signals, not forensic proof.
What makes EyeSift different from other AI voice detectors?
EyeSift is designed for fast private triage: no signup, no email, no server upload, and browser-side checks for waveform and file-quality signals. Some provider classifiers are scoped to one generator or require accounts, so use EyeSift as a first-pass review step alongside source verification.
Do I need an account or email to use the AI voice detector?
No. Select an audio file and run the check in your browser. EyeSift does not require an account, email address, subscription, or server upload for the audio-analysis tool.
What types of AI audio can this detector identify?
EyeSift screens audio for signs that can appear in AI text-to-speech, voice cloning, synthetic narration, AI-generated sound, and heavily processed audio. It checks browser-readable waveform and metadata signals such as duration, bitrate, energy, silence ratio, zero-crossing variation, and micro-variation.
Can EyeSift detect AI-generated sound, not just voices?
EyeSift can screen browser-readable speech, music, sound-effect, podcast, or audiobook clips for synthetic-audio risk signals, but it is not a generic sound-recognition classifier and does not identify what object made a sound. Use it for AI-generated sound triage, then check provenance, provider watermarks, source history, and human review for important decisions.
How does voice clone detection work?
Voice-clone triage looks for file and waveform patterns that differ from natural recordings, such as overly smooth transitions, low dynamic variation, unusual silence ratios, or quality constraints that hide detail. The result is a screening signal and should be combined with source verification for high-stakes decisions.
Can an AI voice detector check scam calls or voice messages?
It can screen a saved voice clip or message for synthetic-audio signals, but it should not be the only verification step. FTC and FBI/IC3 guidance treats AI voice cloning and AI-generated audio as impersonation and vishing risks, while the FCC treats AI-generated robocall voices as artificial or prerecorded voices under the TCPA. For urgent money, account, or identity requests, verify the person through a separate trusted channel before acting.
What audio formats produce the best results?
WAV and FLAC files provide the most data for analysis because they are uncompressed or lossless. MP3, M4A, and OGG files can work when the browser can decode them, but compression can mask useful waveform detail. For best results, use the highest quality audio available and avoid files that have been converted multiple times or recorded from speakers using a phone microphone.
Can this detect AI-generated podcast or audiobook content?
It can screen podcast or audiobook samples when the browser can decode the file. Longer clips usually provide stronger waveform context than very short clips. Premium AI voices and post-production processing can reduce reliability, so results should be considered probabilistic rather than definitive.
How reliable is AI audio detection for legal or forensic use?
AI audio detection tools provide risk estimates, not forensic certainty, and EyeSift's score is a heuristic triage signal rather than a calibrated probability. For legal proceedings or formal investigations, automated detection should be supplemented with expert analysis by audio forensics professionals. Our tool is best suited for preliminary screening, content moderation workflows, and awareness of synthetic audio characteristics.
Is my uploaded audio file stored or transmitted?
No. All audio analysis runs entirely in your browser. Your audio file is never sent to any server, stored in any database, or accessible to anyone else. The file data exists only in your local browser memory for the duration of your session.
Is there a free AI voice detector online?
Yes. EyeSift is a free AI voice detector that runs online in your browser with no signup, email, or upload to a server. It screens MP3, WAV, M4A, OGG, FLAC, and WebM/Opus clips, or a microphone recording, for waveform and file-quality signals associated with synthetic speech. The ElevenLabs AI Speech Classifier is also free and needs no login, but it only detects speech generated with ElevenLabs. Every free result is indicative, not proof.
Can EyeSift detect ElevenLabs voices?
Not specifically. EyeSift is generator-agnostic: it measures duration, bitrate, energy, silence, clipping, crest factor, zero-crossing, and micro-variation, so it can flag some synthetic or heavily processed speech from any system, but it does not decode the watermark ElevenLabs says it embeds and it cannot attribute a clip to ElevenLabs. High-quality ElevenLabs output can pass this screen. For attribution, use the ElevenLabs AI Speech Classifier, which analyzes the first minute of a file and, per ElevenLabs, does not reliably classify audio from its Eleven v3 model.
How accurate are AI voice detectors?
There is no single accuracy number that applies outside a vendor's own test set. Enterprise vendors such as Pindrop and Resemble publish self-reported figures above 90 percent, but research challenges such as ASVspoof have found that detectors lose accuracy on compressed, phone-transmitted, short, or newer-generator audio. EyeSift's score is a heuristic triage signal, not a calibrated probability, so treat any detector output as one input alongside provenance checks and speaker verification.
Does the audio leave my device?
No. EyeSift decodes and measures the file with your browser's Web Audio API on your own device. The clip is not uploaded, stored, or sent to any EyeSift server, and a microphone recording is handled the same way. Vendor classifiers and most free web checkers, by contrast, upload the file to their servers.
What audio formats work?
Any format your browser can decode: WAV and FLAC give the most waveform detail, MP3, M4A, and OGG work well at normal bitrates, and WebM/Opus voice notes decode in most modern browsers. Very low bitrates, multiple re-encodings, and speaker-to-microphone re-recordings reduce reliability, and clips shorter than about five seconds are marked low confidence.
Can I tell if a voice is AI by listening?
Sometimes, but not reliably in 2026. Manual checks such as breath and pause placement, flat or oddly stressed prosody, missing room tone, plosive and sibilance behaviour, background consistency, and identical renderings of repeated phrases can raise suspicion, and our guide on how to tell if a voice is AI-generated walks through eight of them. Combine listening with a detector screen, provenance checks where supported, and verification of the speaker through a known channel.