| --- |
| license: cc-by-nc-sa-4.0 |
| language: [ru] |
| pretty_name: "PyAra — Russian Audio Deepfake Detection" |
| task_categories: [audio-classification] |
| size_categories: [100K<n<1M] |
| configs: |
| - config_name: default |
| data_files: |
| - {split: test, path: "data/test-*.parquet"} |
| tags: |
| - anti-spoofing |
| - audio-deepfake-detection |
| - speech |
| - benchmark |
| - arena-ready |
| - russian |
| arxiv: [] |
| --- |
| |
| # PyAra — Russian Audio Deepfake Detection |
|
|
| Benchmark-ready packaging of **PyAra**, a Russian-language audio anti-spoofing |
| dataset (source: https://www.kaggle.com/datasets/alep079/pyara). |
|
|
| ## Overview |
|
|
| Binary classification: **bonafide** (genuine Russian human recordings) vs. |
| **spoof** (synthetic / converted speech). The spoof side is produced by **five** |
| generation algorithms (`alg_1` … `alg_5`). Label is the top-level source |
| directory (`Real/` → bonafide, `Fake/` → spoof), per the `fake` column of |
| `final_dataset.tsv`. |
|
|
| ## License & redistribution |
|
|
| Released under the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 |
| International (CC BY-NC-SA 4.0)** license. Redistribution and adaptation are |
| permitted for **non-commercial** use with attribution and ShareAlike; this |
| packaging is itself CC BY-NC-SA 4.0. See `LICENSE.txt`. Audio is the original |
| 16 kHz mono WAV, embedded bit-exactly (no re-encode — a full decode probe of all |
| clips passed cleanly). |
|
|
| ## Schema |
|
|
| | Column | Type | Description | |
| |--------|------|-------------| |
| | `path` | `string` | source-relative path, e.g. `Fake/alg_1_0.wav`, unique | |
| | `audio` | `Audio(16000)` | 16 kHz mono WAV | |
| | `label` | `ClassLabel` | `"bonafide"` (0) / `"spoof"` (1) | |
| | `notes` | `string` | JSON: `utterance_id`, `algorithm`, `gender`, `age`, `length` | |
|
|
| `notes` example: |
| ```json |
| {"utterance_id": "alg_1_0", "algorithm": "alg_1", "gender": "male", "age": "twenties", "length": "5.55"} |
| ``` |
|
|
| `utterance_id` is the source filename stem (`real_12713`, `alg_1_0`) — unique |
| across the whole set. |
|
|
| ## Quick Start |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("SpeechAntiSpoofingBenchmarks/PyAra", split="test") |
| print(ds[0]) |
| ``` |
|
|
| ## Stats |
|
|
| | Stat | Value | |
| |------|-------| |
| | Total trials | 201,778 | |
| | Bonafide (real) | 73,583 | |
| | Spoof | 128,195 | |
| | Spoof algorithms | alg_1 (46,505), alg_2 (10,065), alg_3 (11,165), alg_4 (25,412), alg_5 (35,048) | |
| | Language | Russian | |
| | Sample rate | 16 kHz mono | |
| |
| ## Source provenance |
| |
| - Dataset: PyAra, https://www.kaggle.com/datasets/alep079/pyara |
| - No associated academic paper. |
| |
| ## Evaluation |
| |
| For evaluation instructions and submission format, see [`submissions/README.md`](submissions/README.md). |
| |
| ## Citation |
| |
| ``` |
| PyAra — Russian Audio Deepfake Detection dataset. |
| https://www.kaggle.com/datasets/alep079/pyara |
| ``` |
| |
| ## Maintainer |
| |
| Contact: k.n.borodin@mtuci.ru |
| |
