shield DeepfakeDetectionAPI

AI Voice Detector

Detect AI-cloned voices, synthetic speech, and voice deepfakes with advanced audio analysis. Protect against voice fraud and identity theft in real-time.

Try It Now

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Drop audio file or click to upload

WAV, MP3, M4A (max 30 seconds)

98%

Detection Accuracy

3+

Audio Formats

Real-time

Streaming Analysis

Multi

Voice Verification

What We Detect

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AI Voice Cloning

Identifies TTS-generated voices and synthetic deepfakes that replicate real speakers.

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Voice Conversion

Detects voice-to-voice transformations and speaker attribute modifications.

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Spliced Audio

Finds cut-and-paste audio segments and unnatural splicing patterns in recordings.

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Synthetic Speech Patterns

Recognizes robotic artifacts and unnatural speech characteristics in generated audio.

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Emotional Manipulation

Detects AI-altered tone and artificially injected emotional characteristics.

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Speaker Verification

Compares voice samples against baseline profiles for identity authentication.

Use Cases

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Call Centers and Banking

Prevent fraud and account takeover through voice authentication during customer verification calls.

Real-time protection against social engineering attacks

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Podcast and Media Verification

Verify the authenticity of interviews, statements, and audio content before publication.

Maintain audience trust with authentic content

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Legal Evidence Authentication

Authenticate voice recordings as legal evidence and detect deepfakes in litigation proceedings.

Admissible forensic audio analysis

How Voice Analysis Works

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Audio Input

WAV, MP3 uploaded or streamed in real-time

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Feature Extraction

Mel spectrogram + MFCC analysis

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Neural Classification

Transformer model evaluates authenticity

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Confidence Report

Detailed verdict with artifact locations

Pipeline arrows visible on desktop. Processing happens in milliseconds.

Voice Detection API 

import requests

url = "https://api.deepfakedetectionapi.ai/v1/voice/detect"
headers = {"Authorization": "Bearer YOUR_API_KEY"}

with open("audio.wav", "rb") as audio_file:
    files = {"audio": audio_file}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
print(f"Verdict: {result['verdict']}")          # REAL or SYNTHETIC
print(f"Confidence: {result['confidence']:.2%}")  # 0.0 to 1.0
print(f"Score: {result['score']:.2f}")           # -1.0 to 1.0

Response Example

{
  "verdict": "SYNTHETIC",
  "confidence": 0.96,
  "score": 0.87,
  "processing_time_ms": 1240,
  "artifacts": {
    "speech_patterns": 0.92,
    "frequency_anomalies": 0.88,
    "mel_spectrogram": 0.91
  }
}

Frequently Asked Questions

What audio formats does the detector support?

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We support WAV, MP3, M4A, FLAC, and OGG formats. Maximum file size is 30 seconds or 10MB. The detector works best with clear audio at 16kHz or higher sample rates, though it performs reliably with standard quality audio from calls and recordings.

Can it detect real-time voice cloning?

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Yes. Our API supports real-time streaming analysis through WebSocket connections. You can stream audio data and receive verdicts with minimal latency, making it suitable for live call monitoring and voice authentication systems.

How does it handle background noise and acoustic conditions?

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Our model is trained on diverse acoustic conditions including background noise, room reverb, and compression artifacts. Performance remains reliable even in challenging environments like call centers or crowded spaces, though clean audio always yields higher confidence scores.

Protect Against AI Voice Fraud

Start detecting synthetic voices and voice deepfakes today. Get instant verdicts on any audio file with our powerful neural network.