SilencioNetwork/hausa-speech

Hausa Speech Dataset

A protocol sample. 5 contributors, recorded on their own devices in their own environments. Every clip carries origin region / variety, mother tongue, gender, device, OS, recording environment. Small by design — see What this is for below before downloading.

Hours	0.41
Clips	42
Speakers	5
Origin varieties	3
Languages	1
Configs	1
Speaker metadata	origin region / variety, mother tongue, gender, device, OS, recording environment
Audio	48 kHz stereo WAV, as captured
Transcripts	none in this release — human-validated transcription available on demand
Licence	cc-by-nc-4.0

This release ships audio and speaker metadata only — it does not include transcripts.

Human-validated transcription is available on demand for this data. Word-level forced alignment included, as shipped in cebuano-speech and tagalog-filipino-speech. Available for this sample, for a larger subset of the same language, or for commissioned collection — info@silencio.network

What this is for

This release carries no transcripts, so it is not a supervised ASR set and is no longer tagged as one. It is a small protocol sample. Plainly, what it is and is not good for:

• Not suitable for speaker-level or accent-level work. 5 contributors is too few to support conclusions about either, and we would rather say so than have you discover it after downloading.
• Recording-condition preview. Real audio from the Silencio app, captured on contributors' own devices in their own environments, with device, OS and environment logged. Use it to judge acoustic quality before commissioning at scale.
• Schema and pipeline validation. Same field layout as the larger Silencio releases, so a loader written against this sample works against a full delivery.
• Qualitative review of spontaneous speech. Listen to what the collection protocol actually produces.

If you need transcripts, they are available on demand over this data — see below.

Load it

from datasets import load_dataset

ds = load_dataset("SilencioNetwork/hausa-speech", "hausa_nigeria", split="train")
print(ds[0])

Requires pip install "datasets>=4.0" and FFmpeg ≥ 4.

Configs: hausa_nigeria

Speaker and recording metadata

Speaker origin / variety	Speakers	%
Nigeria - Kano	2	40.0%
Nigeria - Katsina	2	40.0%
Nigeria - Nigerian Standard	1	20.0%

Gender	Speakers	%
male	4	80.0%
female	1	20.0%

Ethnicity (self-reported)	Speakers	%
Black or African American	4	80.0%
Other	1	20.0%

Device	Clips	%
Mobile	37	88.1%
Desktop	5	11.9%

Environment	Clips	%
home	34	81.0%
cafe	5	11.9%
outdoor	2	4.8%
restaurant	1	2.4%

Ethnicity is self-reported by the contributor at enrolment, using a fixed category list; it is not inferred from the audio and it is not a label of the speech. It is included because accent and speaker-attribute fairness work needs it, and it is collected under the same consent as the rest of the metadata.

Human-validated transcription — available on demand

This release is not human-transcribed. Silencio provides human transcription with word-level forced alignment on demand, over this sample or over a larger subset of the same language, and as part of commissioned collection.

These releases show exactly what that deliverable looks like — human transcript text, machine forced alignment, per-token start and end times:

• SilencioNetwork/cebuano-speech — Cebuano (Bisaya) Spontaneous Speech
• SilencioNetwork/tagalog-filipino-speech — Tagalog / Filipino Spontaneous Speech

To request transcription over this data or any other Silencio subset: info@silencio.network

Limitations

• Sample scale. 42 clips, 5 speakers, 0.41 hours. This is a demonstration sample, not a training corpus.
• No transcripts. Audio and speaker metadata only. See above.
• Gender imbalance. 4 of 5 speakers are male. Do not use this release for gender-comparative work. Balanced cohorts are available through the collection programme.
• Few speakers. 5 contributors, so speaker-level conclusions are not supportable.
• No acoustic annotation. Recording environment, background-noise class and SNR are not annotated in this release. Available for commissioned collection.
• Audio is 48 kHz stereo WAV as captured. Resample and downmix before batching.
• No baseline. No reference WER is published with this release.

Provenance and consent

Every recording is contributed by an opted-in participant through the Silencio app, under a consent record covering AI/ML training use. Contributors can request deletion, and deletion propagates to downstream releases. Full provenance documentation is available to licensees.

License

cc-by-nc-4.0 — free for research and non-commercial use with attribution.

Attribution string: Silencio Network, Hausa Speech Dataset, 2026. CC BY-NC 4.0.

Non-commercial covers research, evaluation and publication. Benchmarking a commercial product model against this data is a commercial use and needs a licence — ask, it is usually granted for evaluation. Model weights trained on this sample inherit the non-commercial restriction.

Commercial licensing: info@silencio.network

Citation

@misc{silencio_hausa_speech_2026,
  title  = {Hausa Speech Dataset},
  author = {Silencio Network},
  year   = {2026},
  url    = {https://huggingface.co/datasets/SilencioNetwork/hausa-speech}
}

Silencio corpus and collection network

Two distinct figures, because they answer different questions.

Recorded and available off the shelf — audio already collected, with metadata, licensable today:

Hours recorded	127,793
Recordings	9,392,870
Contributors who recorded	222,145
Languages	156
Countries and territories of origin	216

Contributor network available for commissioned collection — registered, consented contributors who can be activated for a specific brief. These are not active contributors to the corpus above; they are the pool it is drawn from and extended through:

Registered contributors	2,000,000+
Countries	180+
Languages reachable	250+

For volume licensing, human transcription over an existing subset, or commissioned collection in a language not listed: info@silencio.network