README.md

---
license: cc-by-nc-nd-4.0
dataset_info:
  features:
  - name: Domain
    dtype: string
  - name: Penjo (Question)
    dtype: string
  - name: Question Code
    dtype: string
  - name: Question Audio
    dtype: audio
  - name: Dwoko (Answer)
    dtype: string
  - name: Answer Code
    dtype: string
  - name: Answer Audio
    dtype: audio
  - name: Voice Contributor
    dtype: string
  splits:
  - name: train
    num_bytes: 125963284
    num_examples: 50
  download_size: 97580275
  dataset_size: 125963284
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- audio
- speech
- civic
- luo
- dholuo
- everyday
- question-answering
- QA
- dataset
pretty_name: luo
size_categories:
- n<1K
---

# Ushauri: A Luo Question-Answer Speech Dataset
 
**Ushauri** is a small, curated speech dataset in [Dholuo (Luo)](https://en.wikipedia.org/wiki/Luo_language) consisting of paired question-and-answer recordings across everyday life domains.

Ushauri is designed to support the development of speech technology that serves the Luo community. The domain coverage (telecommunications, education, agriculture, finance, market, transportation, etc.) reflects everyday areas where accessible voice interfaces could improve access to information and services. Researchers and developers working on civic technology, public service delivery, or digital inclusion for East African communities are encouraged to build on this work.
 
## Dataset Summary
 
- **Language:** Dholuo (Luo) — `luo`
- **Domains:** 10 domains: `Telecommunications`, `Cultural Activities`, `Education`, `Everyday Activities`, `Civil Activities`, `Legal Activities`, `Basic Agriculture`, `Transportation`, `Finance` and `Market`.
- **Total pairs:** 50 question-answer pairs
- **Total audio clips:** 100 (50 questions + 50 answers)
- **Modalities:** text + audio
- **Voice contributors:** anonymized speakers, identified by gender and age range

  > **Note:** Ushauri is a **preview release** — a small, high-quality sample of a larger body of Dholuo speech data. For access to extended datasets, additional speakers, or commissioned collections in Luo and other African languages, see the [License](#license) section.

## Dataset Structure
 
Each row in the dataset contains the following fields:
 
| Column | Type | Description |
|---|---|---|
| `Domain` | string | Ten (10) Topic areas of the question-answer pair, written in Luo with English translation in parentheses. |
| `Penjo (Question)` | string | The question in Luo |
| `Question Code` | string | Unique identifier for the question audio |
| `Question Audio` | audio | Recording of the question |
| `Dwoko (Answer)` | string | The answer in Luo |
| `Answer Code` | string | Unique identifier for the answer audio |
| `Answer Audio` | audio | Recording of the answer |
| `Voice Contributor` | string | Anonymized speaker ID encoding gender and age range |
 
### Code format
 
Question and answer codes follow the pattern `{DOMAIN}-{TYPE}-{NUMBER}`:
 
- `DOMAIN` — two-letter domain identifier (e.g., `TL` = Telecommunications, `CL` = Cultural Activities)
- `TYPE` — `QN` for question, `AN` for answer
- `NUMBER` — two-digit sequence within the domain
Example: `TL-QN-01` is the first question in the Telecommunications domain; its paired answer is `TL-AN-01`.
 
### Voice contributor format
 
Speaker IDs follow the pattern `{ID}_{gender}_{age_range}`, e.g., `001_female_18_to_25`. No personally identifying information is included.
 
### Splits
 
The dataset ships as a single split, which can be used for evaluation.
 
## Usage
 
```python
from datasets import load_dataset
 
ds = load_dataset("tonative/ushauri", split="train")
 
sample = ds[0]
print("Question (Luo):    ", sample["Penjo (Question)"])
print("Answer (Luo):      ", sample["Dwoko (Answer)"])
print("Domain:            ", sample["Domain"])
print("Voice contributor: ", sample["Voice Contributor"])
 
# Access the audio arrays
q_audio = sample["Question Audio"]
a_audio = sample["Answer Audio"]
print("Question audio:", q_audio["array"].shape, "@", q_audio["sampling_rate"], "Hz")
print("Answer audio:  ", a_audio["array"].shape, "@", a_audio["sampling_rate"], "Hz")
```
 
To play a clip in a Jupyter/Colab notebook:
 
```python
from IPython.display import Audio
Audio(sample["Question Audio"]["array"], rate=sample["Question Audio"]["sampling_rate"])
```
 
## Data Collection
 
Questions and answers were written by native Dholuo speakers around common everyday domains, then recorded by voice contributors. The recordings capture natural conversations suitable for Luo language technology research.
 
## Intended Uses
 
- Automatic speech recognition (ASR) for Dholuo
- Text-to-speech (TTS) benchmarking and voice cloning research in low-resource settings
- Spoken and text-based question answering
- Cross-lingual and multilingual NLP research including African languages
- Linguistic and cultural documentation of everyday Luo speech

## Limitations and Considerations
 
- **Small scale.** With 50 QA pairs, Ushauri is intended for evaluation, few-shot learning, and demonstration rather than large-scale model training from scratch.
- **Speaker diversity.** The pool of voice contributors is limited; models trained or evaluated on Ushauri alone may not generalize across all Luo speakers, dialects, or age groups.
- **Domain coverage.** Domains are broad but shallow — a handful of items per topic.
 
## License

This preview dataset is released under the [Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)](https://creativecommons.org/licenses/by-nc-nd/4.0/).

Under this license, you may **download, share, and reference** the dataset for non-commercial purposes with appropriate attribution. You may **not**:

- use the dataset for commercial purposes,
- redistribute modified or derivative versions of the data or recordings,
- incorporate the recordings into commercial products, services, or model training pipelines intended for commercial deployment.

### Commercial use, extended datasets, and custom collections

Ushauri is a **preview release** intended to demonstrate the quality and structure of speech data that [Tonative Africa] can produce. For commercial licensing, larger domain-specific datasets, additional Luo speakers, or new language collections, please contact us via `services@tonative.org`.

## Citation
 
If you use Ushauri in your research, please cite it as:
 
```bibtex
@dataset{tonative_ushauri_2026,
  title     = {Ushauri: A Luo Question-Answer Speech Dataset (Preview)},
  author    = {{Tonative Africa}},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/tonative/ushauri}
}
```
 
A `CITATION.cff` file is provided in the repository root for automatic citation generation.

## Acknowledgments
We gratefully acknowledge the voice contributors who recorded the questions and answers, and the native Dholuo speakers and language experts who wrote and reviewed the source texts. Contributor identities are anonymized in the dataset in accordance with our data handling practices.

## Contact
 
For questions, corrections, or contributions, please open a discussion on the [dataset repository](https://huggingface.co/datasets/tonative/ushauri) or email us directly: `services@tonative.org`