Datasets:
Dataset Viewer
audio
audio | filename
string | category
string | timestamp
string | label
int64 | manipulation_type
string |
---|---|---|---|---|---|
dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_21
|
real
|
0.00-7.92-T
| 1 |
real
|
|
dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_30
|
real
|
0.00-7.92-T
| 1 |
real
|
|
dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_12
|
real
|
0.00-7.36-T
| 1 |
real
|
|
dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_8
|
real
|
0.00-7.08-T
| 1 |
real
|
|
dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_44
|
real
|
0.00-7.04-T
| 1 |
real
|
|
dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_10
|
real
|
0.00-7.00-T
| 1 |
real
|
|
dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_03_baum_64kb_19
|
real
|
0.00-6.96-T
| 1 |
real
|
|
dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_7
|
real
|
0.00-6.84-T
| 1 |
real
|
|
dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_13
|
real
|
0.00-6.80-T
| 1 |
real
|
|
dev_real_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_46
|
real
|
0.00-6.80-T
| 1 |
real
|
|
dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_21
|
edit
|
0.00-4.89-T/4.89-5.19-F/5.19-8.01-T
| 0 |
edit
|
|
dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_30
|
edit
|
0.00-1.09-T/1.09-1.54-F/1.54-7.74-T
| 0 |
edit
|
|
dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_12
|
edit
|
0.00-4.93-T/4.93-5.64-F/5.64-7.47-T
| 0 |
edit
|
|
dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_8
|
edit
|
0.00-0.57-T/0.57-1.08-F/1.08-7.00-T
| 0 |
edit
|
|
dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_44
|
edit
|
0.00-5.92-T/5.92-6.49-F/6.49-6.91-T
| 0 |
edit
|
|
dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_10
|
edit
|
0.00-1.26-T/1.26-1.74-F/1.74-6.89-T
| 0 |
edit
|
|
dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_03_baum_64kb_19
|
edit
|
0.00-0.61-T/0.61-0.94-F/0.94-7.02-T
| 0 |
edit
|
|
dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_7
|
edit
|
0.00-3.34-T/3.34-3.45-F/3.45-6.71-T
| 0 |
edit
|
|
dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_13
|
edit
|
0.00-5.86-T/5.86-6.31-F/6.31-6.95-T
| 0 |
edit
|
|
dev_edit_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_46
|
edit
|
0.00-0.11-T/0.11-0.62-F/0.62-6.77-T
| 0 |
edit
|
|
dev_cut_paste_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_21
|
cut_paste
|
0.00-4.89-T/4.89-5.19-F/5.19-8.01-T
| 0 |
cut_paste
|
|
dev_cut_paste_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_30
|
cut_paste
|
0.00-1.09-T/1.09-1.54-F/1.54-7.74-T
| 0 |
cut_paste
|
|
dev_cut_paste_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_12
|
cut_paste
|
0.00-4.93-T/4.93-5.64-F/5.64-7.47-T
| 0 |
cut_paste
|
|
dev_cut_paste_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_8
|
cut_paste
|
0.00-0.57-T/0.57-1.08-F/1.08-7.00-T
| 0 |
cut_paste
|
|
dev_cut_paste_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_44
|
cut_paste
|
0.00-5.92-T/5.92-6.49-F/6.49-6.91-T
| 0 |
cut_paste
|
|
dev_cut_paste_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_02_baum_64kb_10
|
cut_paste
|
0.00-1.26-T/1.26-1.74-F/1.74-6.89-T
| 0 |
cut_paste
|
|
dev_cut_paste_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_03_baum_64kb_19
|
cut_paste
|
0.00-0.61-T/0.61-0.94-F/0.94-7.02-T
| 0 |
cut_paste
|
|
dev_cut_paste_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_7
|
cut_paste
|
0.00-3.34-T/3.34-3.45-F/3.45-6.71-T
| 0 |
cut_paste
|
|
dev_cut_paste_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_13
|
cut_paste
|
0.00-5.86-T/5.86-6.31-F/6.31-6.95-T
| 0 |
cut_paste
|
|
dev_cut_paste_medium-100-emerald_city_librivox_64kb_mp3-emeraldcity_01_baum_64kb_46
|
cut_paste
|
0.00-0.11-T/0.11-0.62-F/0.62-6.77-T
| 0 |
cut_paste
|
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/
βββ combine/ # Directory containing all audio files (~11,076 files)
β βββ dev_real_medium-*.wav # Authentic audio samples
β βββ dev_edit_medium-*.wav # Edited audio samples
β βββ dev_cut_paste_medium-*.wav # Cut-and-paste manipulated samples
β βββ dev_resyn_medium-*.wav # Resynthesized audio samples
βββ medium_real.txt # Labels for authentic audio (2,769 entries)
βββ medium_edit.txt # Labels for edited audio (2,769 entries)
βββ medium_cut_paste.txt # Labels for cut-paste audio (2,769 entries)
βββ 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 segmentF
= False/Manipulated segmentlabel
: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
This is a joint work done by NVIDIA and National Taiwan University. If you use this dataset, please cite:
@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.
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