Add dataset README documentation

README.md

@@ -1,3 +1,120 @@
----
-license: apache-2.0
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+# SINE Dataset
+
+## Overview
+
+The Speech INfilling Edit (SINE) dataset is a comprehensive collection for speech deepfake detection and audio authenticity verification. This dataset contains ~87GB of audio data distributed across 32 splits, featuring both authentic and synthetically manipulated speech samples.
+
+## Dataset Statistics
+
+- **Total Size**: ~87GB
+- **Number of Splits**: 32 (split-0.tar.gz to split-31.tar.gz)
+- **Audio Format**: WAV files
+- **Source**: Speech edited from LibriLight dataset with transcripts obtained from LibriHeavy
+
+### Audio Statistics
+
+| Audio Types | Subsets | # of Samples | # of Speakers | Durations (h) | Audio Lengths (s) |  |
+|-------------|---------|--------------|---------------|---------------|-------------------|--|
+|             |         |              |               |               | min | max |
+| Real/Resyn  | train   | 26,547       | 70            | 51.82         | 6.00 | 8.00 |
+|             | val     | 8,676        | 100           | 16.98         | 6.00 | 8.00 |
+|             | test    | 8,494        | 900           | 16.60         | 6.00 | 8.00 |
+| Infill/CaP  | train   | 26,546       | 70            | 51.98         | 5.40 | 9.08 |
+|             | val     | 8,686        | 100           | 16.99         | 5.45 | 8.76 |
+|             | test    | 8,493        | 903           | 16.64         | 5.49 | 8.85 |
+
+## Data Structure
+
+Each split (e.g., `split-0/`) contains:
+
+```
+split-X/
+├── combine/                    # Directory containing all audio files (~11,076 files)
+│   ├── dev_real_medium-*.wav          # Authentic audio samples
+│   ├── dev_edit_medium-*.wav          # Edited audio samples
+│   ├── dev_cut_paste_medium-*.wav     # Cut-and-paste manipulated samples
+│   └── dev_resyn_medium-*.wav         # Resynthesized audio samples
+├── medium_real.txt             # Labels for authentic audio (2,769 entries)
+├── medium_edit.txt             # Labels for edited audio (2,769 entries)
+├── medium_cut_paste.txt        # Labels for cut-paste audio (2,769 entries)
+└── medium_resyn.txt            # Labels for resynthesized audio (2,769 entries)
+```
+
+## Audio Categories
+
+### 1. Authentic Speech (`dev_real_medium-*`)
+- Original, unmodified speech recordings from LibriVox audiobooks
+- Labeled as class `1` (authentic)
+- Simple time annotation format: `filename start-end-T label`
+
+### 2. Resynthesized Speech (`dev_resyn_medium-*`)
+- Speech regenerated from mel-spectrogram using HiFi-GAN vocoder
+- Labeled as class `1` (authentic)
+- Simple time annotation format
+
+### 3. Edited Speech (`dev_edit_medium-*`)
+- Audio samples with artificial modifications/edits
+- Labeled as class `0` (manipulated)
+- Complex time annotation with T/F segments indicating real/fake portions
+
+### 4. Cut-and-Paste Speech (`dev_cut_paste_medium-*`)
+- Audio created by cutting and pasting segments from different sources
+- Labeled as class `0` (manipulated)
+- Complex time annotation showing spliced segments
+
+## Label Format
+
+### Simple Format (Real/Resyn)
+```
+filename start_time-end_time-T label
+```
+Example:
+```
+dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_21 0.00-7.92-T 1
+```
+
+### Complex Format (Edit/Cut-Paste)
+```
+filename time_segment1-T/time_segment2-F/time_segment3-T label
+```
+Example:
+```
+dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_21 0.00-4.89-T/4.89-5.19-F/5.19-8.01-T 0
+```
+
+Where:
+- `T` = True/Authentic segment
+- `F` = False/Manipulated segment
+- `label`: `1` = Authentic, `0` = Manipulated
+
+## Applications
+
+This dataset is suitable for:
+
+- **Speech Deepfake Detection**: Binary classification of authentic vs. manipulated speech
+- **Temporal Localization**: Identifying specific time segments that contain manipulations
+- **Manipulation Type Classification**: Distinguishing between different types of audio manipulation
+- **Robustness Testing**: Evaluating detection systems across various manipulation techniques
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@inproceedings{huang2024detecting,
+  title={Detecting the Undetectable: Assessing the Efficacy of Current Spoof Detection Methods Against Seamless Speech Edits},
+  author={Huang, Sung-Feng and Kuo, Heng-Cheng and Chen, Zhehuai and Yang, Xuesong and Yang, Chao-Han Huck and Tsao, Yu and Wang, Yu-Chiang Frank and Lee, Hung-yi and Fu, Szu-Wei},
+  booktitle={2024 IEEE Spoken Language Technology Workshop (SLT)},
+  pages={652--659},
+  year={2024},
+  organization={IEEE}
+}
+```
+
+## License
+
+This dataset is released under the Apache 2.0 License.
+
+---
+
+**Note**: This dataset is intended for research purposes in speech authenticity verification and deepfake detection. Please use responsibly and in accordance with applicable laws and regulations.