tonative-org commited on
Commit
f765296
·
verified ·
1 Parent(s): 4ac4ec4

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +146 -2
README.md CHANGED
@@ -20,13 +20,157 @@ dataset_info:
20
  dtype: string
21
  splits:
22
  - name: train
23
- num_bytes: 125963284.0
24
  num_examples: 50
25
  download_size: 97580275
26
- dataset_size: 125963284.0
27
  configs:
28
  - config_name: default
29
  data_files:
30
  - split: train
31
  path: data/train-*
 
 
 
 
 
 
 
 
 
 
 
 
 
32
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
20
  dtype: string
21
  splits:
22
  - name: train
23
+ num_bytes: 125963284
24
  num_examples: 50
25
  download_size: 97580275
26
+ dataset_size: 125963284
27
  configs:
28
  - config_name: default
29
  data_files:
30
  - split: train
31
  path: data/train-*
32
+ tags:
33
+ - audio
34
+ - speech
35
+ - civic
36
+ - luo
37
+ - dholuo
38
+ - everyday
39
+ - question-answering
40
+ - QA
41
+ - dataset
42
+ pretty_name: luo
43
+ size_categories:
44
+ - n<1K
45
  ---
46
+
47
+ # Ushauri: A Luo Question-Answer Speech Dataset
48
+
49
+ **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.
50
+
51
+ 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.
52
+
53
+ ## Dataset Summary
54
+
55
+ - **Language:** Dholuo (Luo) — `luo`
56
+ - **Domains:** 10 domains: `Telecommunications`, `Cultural Activities`, `Education`, `Everyday Activities`, `Civil Activities`, `Legal Activities`, `Basic Agriculture`, `Transportation`, `Finance` and `Market`.
57
+ - **Total pairs:** 50 question-answer pairs
58
+ - **Total audio clips:** 100 (50 questions + 50 answers)
59
+ - **Modalities:** text + audio
60
+ - **Voice contributors:** anonymized speakers, identified by gender and age range
61
+
62
+ > **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.
63
+
64
+ ## Dataset Structure
65
+
66
+ Each row in the dataset contains the following fields:
67
+
68
+ | Column | Type | Description |
69
+ |---|---|---|
70
+ | `Domain` | string | Ten (10) Topic areas of the question-answer pair, written in Luo with English translation in parentheses. |
71
+ | `Penjo (Question)` | string | The question in Luo |
72
+ | `Question Code` | string | Unique identifier for the question audio |
73
+ | `Question Audio` | audio | Recording of the question |
74
+ | `Dwoko (Answer)` | string | The answer in Luo |
75
+ | `Answer Code` | string | Unique identifier for the answer audio |
76
+ | `Answer Audio` | audio | Recording of the answer |
77
+ | `Voice Contributor` | string | Anonymized speaker ID encoding gender and age range |
78
+
79
+ ### Code format
80
+
81
+ Question and answer codes follow the pattern `{DOMAIN}-{TYPE}-{NUMBER}`:
82
+
83
+ - `DOMAIN` — two-letter domain identifier (e.g., `TL` = Telecommunications, `CL` = Cultural Activities)
84
+ - `TYPE` — `QN` for question, `AN` for answer
85
+ - `NUMBER` — two-digit sequence within the domain
86
+ Example: `TL-QN-01` is the first question in the Telecommunications domain; its paired answer is `TL-AN-01`.
87
+
88
+ ### Voice contributor format
89
+
90
+ Speaker IDs follow the pattern `{ID}_{gender}_{age_range}`, e.g., `001_female_18_to_25`. No personally identifying information is included.
91
+
92
+ ### Splits
93
+
94
+ The dataset ships as a single split, which can be used for evaluation.
95
+
96
+ ## Usage
97
+
98
+ ```python
99
+ from datasets import load_dataset
100
+
101
+ ds = load_dataset("tonative/ushauri", split="train")
102
+
103
+ sample = ds[0]
104
+ print("Question (Luo): ", sample["Penjo (Question)"])
105
+ print("Answer (Luo): ", sample["Dwoko (Answer)"])
106
+ print("Domain: ", sample["Domain"])
107
+ print("Voice contributor: ", sample["Voice Contributor"])
108
+
109
+ # Access the audio arrays
110
+ q_audio = sample["Question Audio"]
111
+ a_audio = sample["Answer Audio"]
112
+ print("Question audio:", q_audio["array"].shape, "@", q_audio["sampling_rate"], "Hz")
113
+ print("Answer audio: ", a_audio["array"].shape, "@", a_audio["sampling_rate"], "Hz")
114
+ ```
115
+
116
+ To play a clip in a Jupyter/Colab notebook:
117
+
118
+ ```python
119
+ from IPython.display import Audio
120
+ Audio(sample["Question Audio"]["array"], rate=sample["Question Audio"]["sampling_rate"])
121
+ ```
122
+
123
+ ## Data Collection
124
+
125
+ 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.
126
+
127
+ ## Intended Uses
128
+
129
+ - Automatic speech recognition (ASR) for Dholuo
130
+ - Text-to-speech (TTS) benchmarking and voice cloning research in low-resource settings
131
+ - Spoken and text-based question answering
132
+ - Cross-lingual and multilingual NLP research including African languages
133
+ - Linguistic and cultural documentation of everyday Luo speech
134
+
135
+ ## Limitations and Considerations
136
+
137
+ - **Small scale.** With 50 QA pairs, Ushauri is intended for evaluation, few-shot learning, and demonstration rather than large-scale model training from scratch.
138
+ - **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.
139
+ - **Domain coverage.** Domains are broad but shallow — a handful of items per topic.
140
+
141
+ ## License
142
+
143
+ 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/).
144
+
145
+ Under this license, you may **download, share, and reference** the dataset for non-commercial purposes with appropriate attribution. You may **not**:
146
+
147
+ - use the dataset for commercial purposes,
148
+ - redistribute modified or derivative versions of the data or recordings,
149
+ - incorporate the recordings into commercial products, services, or model training pipelines intended for commercial deployment.
150
+
151
+ ### Commercial use, extended datasets, and custom collections
152
+
153
+ 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`.
154
+
155
+ ## Citation
156
+
157
+ If you use Ushauri in your research, please cite it as:
158
+
159
+ ```bibtex
160
+ @dataset{tonative_ushauri_2026,
161
+ title = {Ushauri: A Luo Question-Answer Speech Dataset (Preview)},
162
+ author = {{Tonative Africa}},
163
+ year = {2026},
164
+ publisher = {Hugging Face},
165
+ url = {https://huggingface.co/datasets/tonative/ushauri}
166
+ }
167
+ ```
168
+
169
+ A `CITATION.cff` file is provided in the repository root for automatic citation generation.
170
+
171
+ ## Acknowledgments
172
+ 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.
173
+
174
+ ## Contact
175
+
176
+ 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`