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DOVEXAI Nigerian Languages Speech & Translation Dataset (XIMA-2122)
Curated by DOVEXAI LTD (Nigeria) · dovexai.africa · dovexai.io
A provenance-tracked dataset of Nigerian-language voice recordings paired with human transcriptions and translations, built for evaluation and supervised fine-tuning (SFT) of speech and translation models. Every recording is cryptographically receipted, fully anonymized, and quality-gated before release.
Dataset snapshot
| Feature | Detail |
|---|---|
| Split | sample (41 evaluation examples) |
| Audio format | WAV 16 kHz 16-bit PCM mono |
| Recording style | Sequential bilingual parallel corpus (Nigerian English → Local language), Sequential bilingual code-switched corpus, and Monolingual English |
| Languages | Yoruba · Hausa · Igbo · Nigerian English · Nigerian Pidgin |
| Language distribution | Yoruba ▉▉▉▉▉▉ 27% · Hausa ▉▉▉▉▉ 24% · Igbo ▉▉▉▉▉ 24% · Nigerian English ▉▉▉ 12% · Nigerian Pidgin ▉▉▉ 12% |
| Contributor gender | Female 100% (Sample scope) |
| Provenance | Cryptographically receipted, verified manifest |
| License | CC BY 4.0 |
Note: This release is a 41-example evaluation and pipeline verification sample, demonstrating DOVEXAI's end-to-end cryptographic provenance and SFT structure. It is designed for pipeline testing, format validation, and evaluation—not as a standalone training corpus.
Stated Limitations & Intended Use
- Evaluation Sample Scope: This open sample is intentionally limited to 41 clips to demonstrate our data format, transcription standards, and cryptographic verification protocol.
- Demographic Scope: 100% of contributors in this open sample are female speakers. DOVEXAI's full commercial datasets cover gender-balanced, multi-region, and multi-dialect demographics across Nigeria and West Africa.
- Commercial Holdings: Production datasets (thousands of hours) remain unreleased open-source and are available for enterprise licensing and custom AI training.
How to use
from datasets import load_dataset
ds = load_dataset("DOVEXAI/XIMA-2122")
# Play/access audio
sample = ds["sample"][0]
print(sample["audio"]) # {'array': [...], 'sampling_rate': 44100, 'path': ...}
print(sample["text_en_ng"]) # English prompt
print(sample["text_local"]) # Local-language transcription
print(sample["language"]) # e.g. "Yoruba", "Hausa", "Igbo"
Need custom data?
DOVEXAI builds training and evaluation data across every modality - text, audio, image, video, document and multimodal - including collection, transcription, translation, data generation, SFT and RLHF preference data, human evaluation and red-teaming packs. Our differentiated coverage is Nigerian and other African languages, accents and code-switching. XIMA-2122 is a small public sample of that coverage; our unreleased holdings are substantially larger.
- Fastest route: Book a 30-minute scoping call
- Or email: hello@dovexai.africa
Community & Feedback
We'd love to hear from you! If you use this dataset, please share:
- Your feedback on the quality, usefulness, and potential improvements
- Research or projects built with this data
- Contributions - if you'd like to contribute additional recordings, transcriptions, or translations for Nigerian or other African languages
Join the DOVEXAI Early Access Contributor Community via our website at dovexai.africa or dovexai.io.
Dataset columns
| Column | Type | Description |
|---|---|---|
id |
string | Unique sample identifier |
audio |
Audio | The voice recording (playable in the Dataset Viewer) |
text_en_ng |
string | The Nigerian-English prompt that was spoken |
text_local |
string | Verbatim transcription of exactly what the contributor said in the recording, including natural/colloquial spelling and code-switching. This is the form anchored to the audio. |
text_local_standard |
string | (optional) A standardized rendering of the same line. This is a normalized/"clean" version, not necessarily what is heard in the audio. |
language |
string | The language spoken in this clip (e.g. Yoruba, Hausa, Igbo, Nigerian Pidgin, Nigerian English) |
local_lang_key |
string | Machine key for the local language (e.g. yoruba, hausa, igbo, nigerian-pidgin, nigerian-english) |
speech_type |
string | sequential bilingual parallel corpus, sequential bilingual code-switched parallel corpus, or monolingual |
gender |
string | Contributor gender (female across 100% of samples) |
receipt_id |
string | Links the row to its provenance receipt |
audio_sha256 |
string | SHA-256 of the original audio file for integrity verification |
Important: verbatim vs. standardized.
text_localis the ground truth for what was actually spoken and should be used as the transcription label.text_local_standard, when present, is an editorial standardization and may differ from the audio.
Recording structure
Each recording falls into one of three types, indicated by the speech_type column:
1. Sequential bilingual parallel corpus (speech_type = "sequential bilingual parallel corpus")
The contributor first reads the prompt in Nigerian English, then immediately speaks the standard local-language translation in the same clip:
[ Nigerian English sentence ] → [ Hausa / Igbo / Nigerian Pidgin translation ]
This applies to:
- DVX-XIMA-2122-001 (all 10 clips): English → Hausa
- DVX-XIMA-2122-002 (all 10 clips): English → Igbo
- DVX-XIMA-2122-003 clips 2, 7, 8, 9, 10: English → Nigerian Pidgin
2. Sequential bilingual code-switched parallel corpus (speech_type = "sequential bilingual code-switched parallel corpus")
The contributor first reads the English prompt, followed immediately by a natural, intra-sententially code-switched Yoruba translation with cultural loanwords/metaphors, and where applicable, a concluding Yoruba proverb:
[ Nigerian English sentence ] → [ Code-switched Yoruba translation ] (→ [ Yoruba proverb ])
This applies to:
- DVX-XIMA-2122-005 (all 11 clips): English → Code-switched Yoruba (+ Proverbs)
3. Monolingual (speech_type = "monolingual")
The contributor speaks Nigerian English only. There is no local-language translation in the clip.
- DVX-XIMA-2122-003 clips 1, 3, 4, 5, 6: purely Nigerian English
For these recordings, local_lang_key is nigerian-english and text_local contains the same English text.
Additional files
This dataset also ships the following raw files for advanced use cases:
sft.jsonl supervised pairs: audio path → text (raw format)
audio/<receipt_id>/audio_NNN.wav the voice recordings (renamed, no personal info)
receipts/<receipt_id>.json per-contributor, hash-locked provenance receipts
receipts/index.json master manifest (tamper-evident)
Provenance & integrity
- Each receipt lists every source file with its SHA-256 and carries a
receipt_hashcomputed over the receipt's contents;index.jsoncarries anindex_hashover the manifest. Recomputing these detects any tampering. - Audio is shipped unmodified (no denoising, trimming, or normalization), so
the file hash in each receipt matches the released
.wavbyte-for-byte. - Recordings passed an automated noise-floor quality gate before inclusion.
Privacy & consent
- Fully anonymized. Contributors appear only as opaque ids
(
contributor_NNN); real names and original filenames are never included. - Contributors recorded under signed consent and NDA agreements. Those documents are not shipped. Each receipt proves they exist via their SHA-256 hash alone, with no personal data exposed.
License
Released under Creative Commons Attribution 4.0 International (CC BY 4.0). You are free to use, share, and adapt this dataset, including for commercial purposes and for training models, provided you give appropriate credit to DOVEXAI LTD (Nigeria). Full terms: https://creativecommons.org/licenses/by/4.0/
Citation
If you use this dataset in your research, product evaluation, or model training, please cite it as follows:
@misc{dovexai2026xima2122,
author = {DOVEXAI LTD (Nigeria)},
title = {XIMA-2122: Nigerian Languages Speech \& Translation Dataset},
year = {2026},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/datasets/DOVEXAI/XIMA-2122}},
note = {Licensed under CC BY 4.0}
}
Plain text:
DOVEXAI LTD (Nigeria) (2026). XIMA-2122: Nigerian Languages Speech & Translation Dataset. Hugging Face Datasets. https://huggingface.co/datasets/DOVEXAI/XIMA-2122
Contact
For questions or commercial dataset licensing, contact DOVEXAI LTD (Nigeria) via hello@dovexai.africa or schedule a call at https://calendly.com/dovexai-io/30min.
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