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VoxGuard Synthetic Speech Dataset

A dataset of 10,000+ AI-generated (deepfake) speech samples created for training and evaluating deepfake speech detection models.

Dataset Description

Samples ~10,040 synthetic WAV files
Format WAV, 16kHz mono
Generation Voice cloning via Qwen3-TTS (Replicate API)
Source speakers 280+ unique speakers from LibriSpeech
Source subsets clean (train.100, train.360, validation, test) + other (train.500, validation, test)

Generation Process

  1. Downloaded ~10,040 real speech samples from LibriSpeech (2-30s duration, diverse speakers)
  2. Transcribed each sample using OpenAI Whisper (medium)
  3. Generated voice clones using Qwen3-TTS in \ mode:
    • Reference audio: original LibriSpeech sample
    • Reference text: Whisper transcription
    • Target text: one of 100 diverse sentences (news, conversation, instructions, etc.)
  4. Result: synthetic speech that mimics each speaker's voice saying a different sentence

Contents

  • \ - ~10,040 synthetic WAV files
    • \ to \ (original batch, 4-digit naming)
    • \ to \ (extended batch, 5-digit naming)
  • \ - Whisper transcriptions for each source sample

Usage

This dataset is used to train the VoxGuard deepfake detection LoRA adapter, which fine-tunes the DF Arena 1B base model.

Note: Only synthetic (fake) speech is included. The corresponding real speech samples are from LibriSpeech and should be obtained separately.

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