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---
dataset_info:
config_name: zul
features:
- name: audio
dtype:
audio:
sampling_rate: 48000
- name: language
dtype: string
- name: split
dtype: string
- name: audio_id
dtype: string
- name: recorder_uuid
dtype: string
- name: type
dtype: string
- name: system_file_name
dtype: string
- name: file_name
dtype: string
- name: full_path
dtype: string
- name: domain
dtype: string
- name: topic
dtype: string
- name: scenario
dtype: string
- name: transcript
dtype: string
- name: duration
dtype: float64
- name: size_bytes
dtype: int64
- name: microphone_device_id
dtype: string
- name: microphone_label
dtype: string
- name: signal_to_noise_ratio
dtype: float64
- name: document_id
dtype: string
- name: source_document
dtype: string
splits:
- name: dev
num_bytes: 4051375741.6
num_examples: 1668
- name: dev_test
num_bytes: 4342849089.914
num_examples: 1583
- name: train
num_bytes: 70154850373.12
num_examples: 24869
download_size: 65973852543
dataset_size: 78549075204.634
configs:
- config_name: zul
data_files:
- split: dev
path: zul/dev-*
- split: dev_test
path: zul/dev_test-*
- split: train
path: zul/train-*
license: cc-by-4.0
extra_gated_prompt: I agree to use this data with the license conditions and use restrictions.
You agree to NOT USE the data for creating models for any form of text-to-speech
(TTS), voice cloning, voice synthesis, or any technology intended to replicate or
generate human voices.
extra_gated_fields:
Company: text
Country: country
Specific date: date_picker
I want to use this model for:
type: select
options:
- Research
- Education
- label: Other
value: other
I agree to use this data with the license conditions and use restrictions: checkbox
task_categories:
- automatic-speech-recognition
pretty_name: z
size_categories:
- 1M<n<10M
language:
- zu
---
**⚠️ IMPORTANT: Work in Progress**
This dataset is **not final**. Releases and updates will continue until **end of September 2025**.
- **Users must regularly check this repository** for new versions, corrections, and updates.
- For **attribution, benchmarking, and publications**, **always reference the latest available information** (as of September 2025 or later).
- Do **not** cite or benchmark against old/incomplete versions. Use only the most recent release and documentation.
We appreciate your patience while we expand and improve this dataset. **Stay updated by watching this repo.**
# Swivuriso: ZA-African Next Voices
**Swivuriso** is a large-scale multilingual speech dataset targeting over **3000 hours** of audio across **7 South African languages**. The dataset is developed to support **Automatic Speech Recognition (ASR)** and inclusive speech technologies for low-resource African languages. It combines both **scripted** and **unscripted** speech, collected through ethical, community-centered processes.
**Dataset Paper**: [ArXiv](https://arxiv.org/abs/XXXX.XXXXX) - Work in Progress
## Language Coverage
| Language | Target Hours | Released |
|---------------|--------------|------------------|
| isiZulu | 500 | ▇▇▇▇▇▁▁▁▁ 47% |
| isiXhosa | 500 | ▁▁▁▁▁▁▁▁▁▁ 0% |
| Sesotho | 500 | ▁▁▁▁▁▁▁▁▁▁ 0% |
| Setswana | 500 | ▁▁▁▁▁▁▁▁▁▁ 0% |
| Xitsonga | 500 | ▁▁▁▁▁▁▁▁▁▁ 0% |
| isiNdebele | 250 | ▁▁▁▁▁▁▁▁▁▁ 0% |
| Tshivenda | 250 | ▁▁▁▁▁▁▁▁▁▁ 0% |
<!-- _Note: Released reflects the amount of validated, preprocessed, and packaged data._ -->
### Use Restriction:
> The persons whose voices are included in this dataset, and the creators and owners of this dataset* do not give consent in any manner or form to, and strictly prohibit any use of this dataset for any form of text-to-speech (TTS), voice cloning, voice synthesis, or any technology or activity intended to replicate, mimic or generate human voices or any technology or activity resulting in the replication, mimicry or generation of human voices.
This dataset includes scripted and unscripted speech across various domains such as agriculture, health, finance, sports, transport, culture, society, and general topics. It is primarily designed for use in automatic speech recognition (ASR) tasks.
Use of this dataset for any form of text-to-speech (TTS), voice cloning, voice synthesis, or any technology intended to replicate or generate human voices is strictly prohibited.
These restrictions are in place until further notice.
---
You can load a language (e.g., zul) using the 🤗 `datasets` library
```python
from datasets import load_dataset
# Load isiZulu configuration
ds = load_dataset("dsfsi-anv/za-african-next-voices", "zul")
```
## Available Fields
| Field | Description |
| --------------- | ---------------------------------------------------- |
| `audio` | 48kHz mono `.wav` audio file (automatically decoded) |
| `transcript` | Transcribed utterance |
| `recorder_uuid` | Unique speaker ID |
| `type` | Scripted or unscripted |
| `domain` | Thematic domain (e.g., Health, Agriculture, etc.) |
| `duration` | Duration of the clip in seconds |
| `gender` | Speaker gender (if available) |
| `age_range` | Speaker's age group (e.g., 18–29, 30–39) |
| `...`
## Splits
All data is split into:
- `train` (85%)
- `dev` (5%)
- `dev_test` (5%)
- `test` (5%) 🔒 – reserved for future shared tasks/public leaderboards
_All splits are **speaker-disjoint** to ensure reproducibility and avoid data leakage._
---
## License
**Creative Commons Attribution 4.0 International (CC BY 4.0)**
You are free to use, share, and adapt the data—with proper attribution to the South Africa NextVoices team.
## Intended Use
- Training/fine-tuning ASR models
- Developing inclusive speech technology for African users
- Cross-lingual learning and low-resource transfer
- Model evaluation and benchmarking
## ⚠️ Limitations and Ethical Use
- Dialectal diversity and regional accents may not be fully covered
- The dataset is not intended for surveillance or other harmful use
- All use must comply with ethical AI principles
<!-- See [Ethics Statement](./ETHICS.md) for full considerations. -->
---
## Citations
If you use Swivuriso in your work, please cite both of the below:
### Dataset
```
@dataset{za-african-next-voices- 2025,
title = {The South African Next Voices Multilingual Speech Dataset},
author = {Vukosi Marivate and Kayode Olaleye and Sitwala Mundia and Nia Zion Van Wyk and Andinda Bakainga and Unarine Netshifhefhe and Mahmooda Milanzie and Hope Tsholofelo Mogale and Chijioke Okorie and Graham Morrissey and Dale Dunbar and Tsosheletso Chidi and Rooweither Mabuya and Andiswa Bukula and Respect Mlambo and Tebogo Macucwa},
url = {https://huggingface.co/datasets/dsfsi-anv/za-african-next-voices/},
url2 = {https://github.com/dsfsi/za-african-next-voices},
url3 = {https://www.dsfsi.co.za/za-african-next-voices/},
publisher = {Data Science for Social Impact Research Group},
year = {2025},
type = {dataset}
}
```
### Research Paper
Will be available soon.
```
@dataset{swivuriso2025,
title = {Swivuriso: Creating the South African Next Voices Multilingual Speech Dataset},
author = {Vukosi Marivate and Kayode Olaleye and Sitwala Mundia and Nia Zion Van Wyk and Andinda Bakainga and Unarine Netshifhefhe and Mahmooda Milanzie and Hope Tsholofelo Mogale and Chijioke Okorie and Graham Morrissey and Dale Dunbar and Tsosheletso Chidi and Rooweither Mabuya and Andiswa Bukula and Respect Mlambo and Tebogo Macucwa},
url = {TBD},
year = {2025},
}
```