| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| pretty_name: EmoFake Test |
| task_categories: |
| - audio-classification |
| size_categories: |
| - 10K<n<100K |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: data/test-*.parquet |
| tags: |
| - anti-spoofing |
| - audio-deepfake-detection |
| - speech |
| - benchmark |
| - arena-ready |
| arxiv: |
| - "2211.05363" |
| --- |
| |
| # EmoFake Test |
|
|
| Benchmark-ready packaging of the EmoFake test set for speech anti-spoofing. |
|
|
| ## Overview |
|
|
| Emotional speech deepfake detection test set. Contains bonafide emotional utterances and spoofed samples with emotion conversion. |
|
|
| ## License |
|
|
| CC BY 4.0. See LICENSE.txt. |
|
|
| ## Schema |
|
|
| | Column | Type | Description | |
| |--------|------|-------------| |
| | path | string | Audio filename | |
| | audio | Audio(16000) | Audio waveform, 16 kHz mono | |
| | label | ClassLabel | bonafide (index 0) or spoof (index 1) | |
| | notes | string | JSON with utterance_id, speaker_id, emotion, method, subset | |
|
|
| notes example: |
| {"utterance_id": "0014_Surprise_001539", "speaker_id": "0014", "emotion": "Surprise", "subset": "test"} |
|
|
| ## Quick Start |
|
|
| from datasets import load_dataset |
| ds = load_dataset("SpeechAntiSpoofingBenchmarks/EmoFake_test", split="test") |
| print(ds[0]) |
| |
| ## Stats |
|
|
| | Stat | Value | |
| |------|-------| |
| | Total trials | 17500 | |
| | Bonafide | 3500 | |
| | Spoof | 14000 | |
|
|
| ## Source provenance |
|
|
| - Paper: https://arxiv.org/abs/2211.05363 |
|
|
| ## Maintainer |
|
|
| Maintained by Kirill Borodin (SpeechAntiSpoofingBenchmarks). |
| - Email: kborodin.research@gmail.com |
| - Telegram: [@korallll_ai](https://t.me/korallll_ai) |
|
|
