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Jabberjay 🦜

One API. Every state-of-the-art synthetic voice detector.

PyPI CI Python License: MIT

Synthetic voice detection is a fragmented landscape — state-of-the-art models are scattered across research repositories, each with its own dependencies, input formats, and output conventions. Jabberjay brings them all under one consistent Python API and CLI so you can detect AI-generated speech without wrestling with model internals.

Features

  • Seven model families — ViT, AST, Wav2Vec2, HuBERT, WavLM, RawNet2, and a classical baseline
  • Unified output — every model returns the same DetectionResult with label, confidence, and scores
  • Zero boilerplate — pass a file path, get a verdict; models are downloaded and cached automatically
  • Flexible — use strings for quick experiments, enums for IDE autocomplete, or pre-load audio to run multiple models on the same clip

Quick start

pip install jabberjay

from Jabberjay import Jabberjay

jj = Jabberjay()
result = jj.detect("interview.wav")
print(result)  # Bonafide ✔️ (94.1% confidence, model=VIT)

Or from the command line:

jabberjay interview.wav
jabberjay suspicious.wav -m HuBERT

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