---
license: cc-by-4.0
language:
  - es
pretty_name: HABLA
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:
  - "10.21437/Interspeech.2023-2272"
---

# HABLA

Benchmark-ready packaging of **HABLA** — *HABLA: A Dataset of Latin American Spanish Accents for Voice Anti-spoofing* (Tamayo Flórez, Manrique & Pereira Nunes, Interspeech 2023). The first voice anti-spoofing collection in **Spanish**, covering five Latin-American accents (Argentina, Chile, Colombia, Peru, Venezuela).

## Overview

The task is binary classification: **bonafide** (genuine human Spanish speech) vs. **spoof** (synthetic / converted speech). Bonafide audio is real Latin-American Spanish; spoof audio is produced by several generators:

- **CycleGAN**, **Diff**(usion), **StarGAN** — voice-conversion across accent pairs (e.g. `Argentina-Chile`).
- **TTS** — text-to-speech.
- **TTS-Diff**, **TTS-StarGAN** — TTS output further passed through a Diff / StarGAN voice-conversion stage (the `TTS-VC` cascade).

## License & redistribution

Redistributed under the **Creative Commons Attribution 4.0 International (CC BY 4.0)** license — the upstream HABLA license. See `LICENSE.txt`. CC BY 4.0 permits redistribution and derivative works with attribution. Labels and the evaluation protocol are unmodified; audio is shipped as the **verbatim source 16 kHz mono PCM WAV** (no re-encode — a whole-set decode probe confirmed every clip is already 16 kHz mono).

## Schema

| Column | Type | Description |
|--------|------|-------------|
| `path` | `string` | source-relative path of the clip, unique |
| `audio` | `Audio(16000)` | 16 kHz mono |
| `label` | `ClassLabel` | `"bonafide"` (0) / `"spoof"` (1) |
| `notes` | `string` | JSON: `utterance_id`, `speaker_id`, `system`, `source_subdir` |

`utterance_id` is the on-disk filename stem (globally unique across all six dirs). `system` is the spoof generator (`CycleGAN` / `Diff` / `StarGAN` / `TTS` / `TTS-Diff` / `TTS-StarGAN`) or `real` for bonafide.

`notes` example:
```json
{"utterance_id": "CycleGAN-arf_00295_00101634363-arf_02121_002402", "speaker_id": "arf_00295", "system": "CycleGAN", "source_subdir": "CycleGAN/Argentina-Argentina/arf_00295-arf_02121"}
```

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("SpeechAntiSpoofingBenchmarks/HABLA", split="test")
print(ds[0])
```

## Stats

| Stat | Value |
|------|-------|
| Total trials | 80,816 |
| Bonafide | 22,816 |
| Spoof | 58,000 |
| CycleGAN | 16,000 |
| Diff | 16,000 |
| StarGAN | 16,000 |
| TTS | 5,000 |
| TTS-Diff | 2,500 |
| TTS-StarGAN | 2,500 |

## Source provenance

- Paper: https://www.isca-archive.org/interspeech_2023/tamayoflorez23_interspeech.html (DOI `10.21437/Interspeech.2023-2272`)
- Protocol: `protocol.txt` (format: `SPEAKER_ID AUDIO_FILE_ID - SYSTEM KEY`)
- Accents: Argentina, Chile, Colombia, Peru, Venezuela. Conversion systems operate across source→target accent pairs.

## Evaluation

For evaluation instructions and submission format, see [`submissions/README.md`](submissions/README.md).

## Citation

```bibtex
@inproceedings{tamayoflorez23_interspeech,
  title     = {{HABLA: A Dataset of Latin American Spanish Accents for Voice Anti-spoofing}},
  author    = {Pablo Andrés {Tamayo Flórez} and Rubén Manrique and Bernardo {Pereira Nunes}},
  year      = {2023},
  booktitle = {{Interspeech 2023}},
  pages     = {1963--1967},
  doi       = {10.21437/Interspeech.2023-2272},
  issn      = {2958-1796},
}
```

## Maintainer

Maintained by Kirill Borodin (SpeechAntiSpoofingBenchmarks).
- Email: ~~k.n.borodin@mtuci.ru~~ (deprecated — use kborodin.research@gmail.com)
- Telegram: [@korallll_ai](https://t.me/korallll_ai)