| # Full LibriSpeech Copy–Move Forgery Dataset |
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| ## 📘 Overview |
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| The **Full LibriSpeech Copy–Move Forgery Dataset** is designed for advancing research in **audio forgery detection** and **tampering localization**. It focuses on the challenging task of **copy–move forgeries**, where segments from a single audio recording are duplicated and relocated within the same file. |
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| The dataset provides speaker-disjoint splits, detailed temporal annotations, and multiple levels of forgery intensity to ensure reproducible and fair evaluation of modern deep learning models. |
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| ## 🧩 Dataset Details |
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| | Property | Description | |
| | ------------------ | -------------------------------------------- | |
| | **Source** | Derived from the clean subset of LibriSpeech | |
| | **Total Samples** | 57,078 | |
| | **Forgery Levels** | 3 (weak, medium, strong) | |
| | **Splits** | Train / Validation / Test (speaker-disjoint) | |
| | **Annotations** | Start–end timestamps for forged regions | |
| | **Features** | Mel-spectrograms | |
| | **Size** | ~25 GB | |
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| ## ⚙️ Usage |
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| You can directly load this dataset using the `datasets` library: |
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| ```python |
| from datasets import load_dataset |
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| dataset = load_dataset("TheAnalyzer/Full-LibriSpeech-CopyMove-Forgery-Dataset") |
| print(dataset) |
| ``` |
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| Or clone the dataset using Git LFS: |
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| ```bash |
| git lfs install |
| git clone https://huggingface.co/datasets/TheAnalyzer/Full-LibriSpeech-CopyMove-Forgery-Dataset |
| ``` |
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| ## 🧠 Baseline Implementation |
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| The baseline CNN-based model, preprocessing pipeline, and evaluation scripts can be found in the companion GitHub repository: |
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| 👉 [https://github.com/RDisCoding/Full-LibriSpeech-CopyMove-Forgery-Dataset](https://github.com/RDisCoding/Full-LibriSpeech-CopyMove-Forgery-Dataset) |
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| ## 📬 Contact |
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| For questions or collaborations, please contact: **[rdiscoding@gmail.com](mailto:rdiscoding@gmail.com)** |
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