README.md

---
pretty_name: Sunbird Speech Benchmark
license: other
license_name: mixed-source-licenses
language:
- ach
- afr
- aka
- amh
- bam
- bem
- ber
- cgg
- dag
- dga
- eng
- ewe
- fra
- ful
- hau
- ibo
- kab
- kau
- kik
- kin
- kln
- koo
- kpo
- led
- lgg
- lin
- lth
- lug
- luo
- luy
- mlg
- myx
- nbl
- nya
- nyn
- orm
- pcm
- ruc
- rwm
- sna
- som
- sot
- swa
- teo
- tsn
- ttj
- wol
- xho
- xog
- yor
- zul
task_categories:
- automatic-speech-recognition
tags:
- speech
- asr
- african-languages
- benchmark
- multilingual
size_categories:
- 10K<n<100K
dataset_info:
  features:
  - name: id
    dtype: string
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: text
    dtype: string
  - name: duration
    dtype: float64
  - name: language
    dtype: string
  - name: language_name
    dtype: string
  - name: subset
    dtype: string
  - name: source
    dtype: string
  splits:
  - name: test
    num_examples: 20213
configs:
- config_name: all
  default: true
  data_files:
  - split: test
    path: data/*/*.parquet
- config_name: ach
  data_files:
  - split: test
    path: data/ach_*/*.parquet
- config_name: afr
  data_files:
  - split: test
    path: data/afr_*/*.parquet
- config_name: aka
  data_files:
  - split: test
    path: data/aka_*/*.parquet
- config_name: amh
  data_files:
  - split: test
    path: data/amh_*/*.parquet
- config_name: bam
  data_files:
  - split: test
    path: data/bam_*/*.parquet
- config_name: bem
  data_files:
  - split: test
    path: data/bem_*/*.parquet
- config_name: ber
  data_files:
  - split: test
    path: data/ber_*/*.parquet
- config_name: cgg
  data_files:
  - split: test
    path: data/cgg_*/*.parquet
- config_name: dag
  data_files:
  - split: test
    path: data/dag_*/*.parquet
- config_name: dga
  data_files:
  - split: test
    path: data/dga_*/*.parquet
- config_name: eng
  data_files:
  - split: test
    path: data/eng_*/*.parquet
- config_name: ewe
  data_files:
  - split: test
    path: data/ewe_*/*.parquet
- config_name: fra
  data_files:
  - split: test
    path: data/fra_*/*.parquet
- config_name: ful
  data_files:
  - split: test
    path: data/ful_*/*.parquet
- config_name: hau
  data_files:
  - split: test
    path: data/hau_*/*.parquet
- config_name: ibo
  data_files:
  - split: test
    path: data/ibo_*/*.parquet
- config_name: kab
  data_files:
  - split: test
    path: data/kab_*/*.parquet
- config_name: kau
  data_files:
  - split: test
    path: data/kau_*/*.parquet
- config_name: kik
  data_files:
  - split: test
    path: data/kik_*/*.parquet
- config_name: kin
  data_files:
  - split: test
    path: data/kin_*/*.parquet
- config_name: kln
  data_files:
  - split: test
    path: data/kln_*/*.parquet
- config_name: koo
  data_files:
  - split: test
    path: data/koo_*/*.parquet
- config_name: kpo
  data_files:
  - split: test
    path: data/kpo_*/*.parquet
- config_name: led
  data_files:
  - split: test
    path: data/led_*/*.parquet
- config_name: lgg
  data_files:
  - split: test
    path: data/lgg_*/*.parquet
- config_name: lin
  data_files:
  - split: test
    path: data/lin_*/*.parquet
- config_name: lth
  data_files:
  - split: test
    path: data/lth_*/*.parquet
- config_name: lug
  data_files:
  - split: test
    path: data/lug_*/*.parquet
- config_name: luo
  data_files:
  - split: test
    path: data/luo_*/*.parquet
- config_name: luy
  data_files:
  - split: test
    path: data/luy_*/*.parquet
- config_name: mlg
  data_files:
  - split: test
    path: data/mlg_*/*.parquet
- config_name: myx
  data_files:
  - split: test
    path: data/myx_*/*.parquet
- config_name: nbl
  data_files:
  - split: test
    path: data/nbl_*/*.parquet
- config_name: nya
  data_files:
  - split: test
    path: data/nya_*/*.parquet
- config_name: nyn
  data_files:
  - split: test
    path: data/nyn_*/*.parquet
- config_name: orm
  data_files:
  - split: test
    path: data/orm_*/*.parquet
- config_name: pcm
  data_files:
  - split: test
    path: data/pcm_*/*.parquet
- config_name: ruc
  data_files:
  - split: test
    path: data/ruc_*/*.parquet
- config_name: rwm
  data_files:
  - split: test
    path: data/rwm_*/*.parquet
- config_name: sna
  data_files:
  - split: test
    path: data/sna_*/*.parquet
- config_name: som
  data_files:
  - split: test
    path: data/som_*/*.parquet
- config_name: sot
  data_files:
  - split: test
    path: data/sot_*/*.parquet
- config_name: swa
  data_files:
  - split: test
    path: data/swa_*/*.parquet
- config_name: teo
  data_files:
  - split: test
    path: data/teo_*/*.parquet
- config_name: tsn
  data_files:
  - split: test
    path: data/tsn_*/*.parquet
- config_name: ttj
  data_files:
  - split: test
    path: data/ttj_*/*.parquet
- config_name: wol
  data_files:
  - split: test
    path: data/wol_*/*.parquet
- config_name: xho
  data_files:
  - split: test
    path: data/xho_*/*.parquet
- config_name: xog
  data_files:
  - split: test
    path: data/xog_*/*.parquet
- config_name: yor
  data_files:
  - split: test
    path: data/yor_*/*.parquet
- config_name: zul
  data_files:
  - split: test
    path: data/zul_*/*.parquet
- config_name: ach_salt
  data_files:
  - split: test
    path: data/ach_salt/*.parquet
- config_name: ach_waxal
  data_files:
  - split: test
    path: data/ach_waxal/*.parquet
- config_name: afr_afrikaans30s
  data_files:
  - split: test
    path: data/afr_afrikaans30s/*.parquet
- config_name: afr_commonvoice
  data_files:
  - split: test
    path: data/afr_commonvoice/*.parquet
- config_name: afr_fleurs
  data_files:
  - split: test
    path: data/afr_fleurs/*.parquet
- config_name: afr_makbenchmark
  data_files:
  - split: test
    path: data/afr_makbenchmark/*.parquet
- config_name: aka_waxal
  data_files:
  - split: test
    path: data/aka_waxal/*.parquet
- config_name: amh_commonvoice
  data_files:
  - split: test
    path: data/amh_commonvoice/*.parquet
- config_name: amh_kyagaba
  data_files:
  - split: test
    path: data/amh_kyagaba/*.parquet
- config_name: amh_makbenchmark
  data_files:
  - split: test
    path: data/amh_makbenchmark/*.parquet
- config_name: amh_shunyalabs
  data_files:
  - split: test
    path: data/amh_shunyalabs/*.parquet
- config_name: amh_waxal
  data_files:
  - split: test
    path: data/amh_waxal/*.parquet
- config_name: bam_makbenchmark
  data_files:
  - split: test
    path: data/bam_makbenchmark/*.parquet
- config_name: bam_robotsbambari
  data_files:
  - split: test
    path: data/bam_robotsbambari/*.parquet
- config_name: bam_robotsmali
  data_files:
  - split: test
    path: data/bam_robotsmali/*.parquet
- config_name: bem_csikasote
  data_files:
  - split: test
    path: data/bem_csikasote/*.parquet
- config_name: bem_makbenchmark
  data_files:
  - split: test
    path: data/bem_makbenchmark/*.parquet
- config_name: ber_tutlay
  data_files:
  - split: test
    path: data/ber_tutlay/*.parquet
- config_name: cgg_commonvoice
  data_files:
  - split: test
    path: data/cgg_commonvoice/*.parquet
- config_name: dag_commonvoice
  data_files:
  - split: test
    path: data/dag_commonvoice/*.parquet
- config_name: dag_waxal
  data_files:
  - split: test
    path: data/dag_waxal/*.parquet
- config_name: dga_waxal
  data_files:
  - split: test
    path: data/dga_waxal/*.parquet
- config_name: eng_intronhealth
  data_files:
  - split: test
    path: data/eng_intronhealth/*.parquet
- config_name: eng_salt
  data_files:
  - split: test
    path: data/eng_salt/*.parquet
- config_name: ewe_makbenchmark
  data_files:
  - split: test
    path: data/ewe_makbenchmark/*.parquet
- config_name: ewe_waxal
  data_files:
  - split: test
    path: data/ewe_waxal/*.parquet
- config_name: fra_gigant
  data_files:
  - split: test
    path: data/fra_gigant/*.parquet
- config_name: ful_fleurs
  data_files:
  - split: test
    path: data/ful_fleurs/*.parquet
- config_name: ful_makbenchmark
  data_files:
  - split: test
    path: data/ful_makbenchmark/*.parquet
- config_name: ful_waxal
  data_files:
  - split: test
    path: data/ful_waxal/*.parquet
- config_name: hau_africanvoices
  data_files:
  - split: test
    path: data/hau_africanvoices/*.parquet
- config_name: hau_clearglobal
  data_files:
  - split: test
    path: data/hau_clearglobal/*.parquet
- config_name: hau_commonvoice
  data_files:
  - split: test
    path: data/hau_commonvoice/*.parquet
- config_name: hau_fleurs
  data_files:
  - split: test
    path: data/hau_fleurs/*.parquet
- config_name: hau_makbenchmark
  data_files:
  - split: test
    path: data/hau_makbenchmark/*.parquet
- config_name: hau_naijavoices
  data_files:
  - split: test
    path: data/hau_naijavoices/*.parquet
- config_name: ibo_africanvoices
  data_files:
  - split: test
    path: data/ibo_africanvoices/*.parquet
- config_name: ibo_commonvoice
  data_files:
  - split: test
    path: data/ibo_commonvoice/*.parquet
- config_name: ibo_fleurs
  data_files:
  - split: test
    path: data/ibo_fleurs/*.parquet
- config_name: ibo_makbenchmark
  data_files:
  - split: test
    path: data/ibo_makbenchmark/*.parquet
- config_name: ibo_naijavoices
  data_files:
  - split: test
    path: data/ibo_naijavoices/*.parquet
- config_name: kab_commonvoice
  data_files:
  - split: test
    path: data/kab_commonvoice/*.parquet
- config_name: kau_clearglobal
  data_files:
  - split: test
    path: data/kau_clearglobal/*.parquet
- config_name: kik_anvkekikuyu
  data_files:
  - split: test
    path: data/kik_anvkekikuyu/*.parquet
- config_name: kin_commonvoice
  data_files:
  - split: test
    path: data/kin_commonvoice/*.parquet
- config_name: kin_makbenchmark
  data_files:
  - split: test
    path: data/kin_makbenchmark/*.parquet
- config_name: kln_ankekalenjin
  data_files:
  - split: test
    path: data/kln_ankekalenjin/*.parquet
- config_name: kln_commonvoice
  data_files:
  - split: test
    path: data/kln_commonvoice/*.parquet
- config_name: koo_commonvoice
  data_files:
  - split: test
    path: data/koo_commonvoice/*.parquet
- config_name: kpo_waxal
  data_files:
  - split: test
    path: data/kpo_waxal/*.parquet
- config_name: led_commonvoice
  data_files:
  - split: test
    path: data/led_commonvoice/*.parquet
- config_name: lgg_salt
  data_files:
  - split: test
    path: data/lgg_salt/*.parquet
- config_name: lin_fleurs
  data_files:
  - split: test
    path: data/lin_fleurs/*.parquet
- config_name: lin_kasuletrev
  data_files:
  - split: test
    path: data/lin_kasuletrev/*.parquet
- config_name: lin_shunyalabs
  data_files:
  - split: test
    path: data/lin_shunyalabs/*.parquet
- config_name: lin_waxal
  data_files:
  - split: test
    path: data/lin_waxal/*.parquet
- config_name: lth_commonvoice
  data_files:
  - split: test
    path: data/lth_commonvoice/*.parquet
- config_name: lug_commonvoice
  data_files:
  - split: test
    path: data/lug_commonvoice/*.parquet
- config_name: lug_fleurs
  data_files:
  - split: test
    path: data/lug_fleurs/*.parquet
- config_name: lug_makbenchmark
  data_files:
  - split: test
    path: data/lug_makbenchmark/*.parquet
- config_name: lug_makerereradio
  data_files:
  - split: test
    path: data/lug_makerereradio/*.parquet
- config_name: lug_salt
  data_files:
  - split: test
    path: data/lug_salt/*.parquet
- config_name: lug_waxal
  data_files:
  - split: test
    path: data/lug_waxal/*.parquet
- config_name: luo_anvkeluo
  data_files:
  - split: test
    path: data/luo_anvkeluo/*.parquet
- config_name: luo_commonvoice
  data_files:
  - split: test
    path: data/luo_commonvoice/*.parquet
- config_name: luo_fleurs
  data_files:
  - split: test
    path: data/luo_fleurs/*.parquet
- config_name: luy_digitaldivide
  data_files:
  - split: test
    path: data/luy_digitaldivide/*.parquet
- config_name: mlg_waxal
  data_files:
  - split: test
    path: data/mlg_waxal/*.parquet
- config_name: myx_waxal
  data_files:
  - split: test
    path: data/myx_waxal/*.parquet
- config_name: nbl_nextvoices
  data_files:
  - split: test
    path: data/nbl_nextvoices/*.parquet
- config_name: nya_fleurs
  data_files:
  - split: test
    path: data/nya_fleurs/*.parquet
- config_name: nya_michsethowusu
  data_files:
  - split: test
    path: data/nya_michsethowusu/*.parquet
- config_name: nyn_salt
  data_files:
  - split: test
    path: data/nyn_salt/*.parquet
- config_name: nyn_waxal
  data_files:
  - split: test
    path: data/nyn_waxal/*.parquet
- config_name: orm_fleurs
  data_files:
  - split: test
    path: data/orm_fleurs/*.parquet
- config_name: orm_makbenchmark
  data_files:
  - split: test
    path: data/orm_makbenchmark/*.parquet
- config_name: orm_waxal
  data_files:
  - split: test
    path: data/orm_waxal/*.parquet
- config_name: pcm_africanvoices
  data_files:
  - split: test
    path: data/pcm_africanvoices/*.parquet
- config_name: pcm_commonvoice
  data_files:
  - split: test
    path: data/pcm_commonvoice/*.parquet
- config_name: ruc_commonvoice
  data_files:
  - split: test
    path: data/ruc_commonvoice/*.parquet
- config_name: rwm_commonvoice
  data_files:
  - split: test
    path: data/rwm_commonvoice/*.parquet
- config_name: sna_fleurs
  data_files:
  - split: test
    path: data/sna_fleurs/*.parquet
- config_name: sna_makbenchmark
  data_files:
  - split: test
    path: data/sna_makbenchmark/*.parquet
- config_name: sna_waxal
  data_files:
  - split: test
    path: data/sna_waxal/*.parquet
- config_name: som_anvkesomali
  data_files:
  - split: test
    path: data/som_anvkesomali/*.parquet
- config_name: som_fleurs
  data_files:
  - split: test
    path: data/som_fleurs/*.parquet
- config_name: som_skydheere
  data_files:
  - split: test
    path: data/som_skydheere/*.parquet
- config_name: sot_fleurs
  data_files:
  - split: test
    path: data/sot_fleurs/*.parquet
- config_name: sot_nextvoices
  data_files:
  - split: test
    path: data/sot_nextvoices/*.parquet
- config_name: swa_commonvoice
  data_files:
  - split: test
    path: data/swa_commonvoice/*.parquet
- config_name: swa_fleurs
  data_files:
  - split: test
    path: data/swa_fleurs/*.parquet
- config_name: teo_salt
  data_files:
  - split: test
    path: data/teo_salt/*.parquet
- config_name: tsn_commonvoice
  data_files:
  - split: test
    path: data/tsn_commonvoice/*.parquet
- config_name: tsn_nextvoices
  data_files:
  - split: test
    path: data/tsn_nextvoices/*.parquet
- config_name: ttj_commonvoice
  data_files:
  - split: test
    path: data/ttj_commonvoice/*.parquet
- config_name: wol_fleurs
  data_files:
  - split: test
    path: data/wol_fleurs/*.parquet
- config_name: wol_kallama
  data_files:
  - split: test
    path: data/wol_kallama/*.parquet
- config_name: wol_makbenchmark
  data_files:
  - split: test
    path: data/wol_makbenchmark/*.parquet
- config_name: xho_fleurs
  data_files:
  - split: test
    path: data/xho_fleurs/*.parquet
- config_name: xho_makbenchmark
  data_files:
  - split: test
    path: data/xho_makbenchmark/*.parquet
- config_name: xho_nextvoices
  data_files:
  - split: test
    path: data/xho_nextvoices/*.parquet
- config_name: xog_waxal
  data_files:
  - split: test
    path: data/xog_waxal/*.parquet
- config_name: yor_africanvoices
  data_files:
  - split: test
    path: data/yor_africanvoices/*.parquet
- config_name: yor_commonvoice
  data_files:
  - split: test
    path: data/yor_commonvoice/*.parquet
- config_name: yor_fleurs
  data_files:
  - split: test
    path: data/yor_fleurs/*.parquet
- config_name: yor_makbenchmark
  data_files:
  - split: test
    path: data/yor_makbenchmark/*.parquet
- config_name: yor_naijavoices
  data_files:
  - split: test
    path: data/yor_naijavoices/*.parquet
- config_name: zul_fleurs
  data_files:
  - split: test
    path: data/zul_fleurs/*.parquet
- config_name: zul_makbenchmark
  data_files:
  - split: test
    path: data/zul_makbenchmark/*.parquet
- config_name: zul_nextvoices
  data_files:
  - split: test
    path: data/zul_nextvoices/*.parquet
---

# Sunbird Speech Benchmark

A multilingual automatic speech recognition (ASR) test set for **51 languages spoken in Africa**:
**20,213 utterances** (64.8 hours) drawn from **110 subsets** of **24 source corpora**.

This is the exact set of clips used to evaluate
[`Sunbird/SunflowerASR-51-african-languages`](https://huggingface.co/Sunbird/SunflowerASR-51-african-languages) (SunflowerASR) and the systems it
was compared against (Gemini, GPT-4o Transcribe, Omnilingual ASR). Freezing the clips in one
repository means every model can be scored on identical audio and references, and the
per-language row counts reproduce the `n_examples` of the published results.

**Languages:** Acholi (`ach`), Afrikaans (`afr`), Akan (`aka`), Amharic (`amh`), Ateso (`teo`), Bambara (`bam`), Bemba (`bem`), Berber (`ber`), Chichewa (`nya`), Dagaare (`dga`), Dagbani (`dag`), English (`eng`), Ewe (`ewe`), French (`fra`), Fulani (`ful`), Hausa (`hau`), Igbo (`ibo`), Ikposo (`kpo`), Kabyle (`kab`), Kalenjin (`kln`), Kanuri (`kau`), Kikuyu (`kik`), Kinyarwanda (`kin`), Kwamba (`rwm`), Lendu (`led`), Lingala (`lin`), Luganda (`lug`), Lugbara (`lgg`), Luhya (`luy`), Lumasaba (`myx`), Luo (`luo`), Lusoga (`xog`), Malagasy (`mlg`), Ndebele (`nbl`), Nigerian Pidgin (`pcm`), Oromo (`orm`), Rukiga (`cgg`), Rukonjo (`koo`), Runyankole (`nyn`), Ruruuli (`ruc`), Rutooro (`ttj`), Shona (`sna`), Somali (`som`), Sotho (`sot`), Swahili (`swa`), Thur (`lth`), Tswana (`tsn`), Wolof (`wol`), Xhosa (`xho`), Yoruba (`yor`), Zulu (`zul`).

## Quick start

```python
from datasets import load_dataset, Audio

# Everything (20,213 rows)
ds = load_dataset("Sunbird/speech-benchmark", split="test")

# One language, e.g. Luganda (all of its source subsets)
lug = load_dataset("Sunbird/speech-benchmark", "lug", split="test")

# One source subset, named as in Sunbird/speech
lug_salt = load_dataset("Sunbird/speech-benchmark", "lug_salt", split="test")

# Audio is stored in its original encoding and resampled to 16 kHz on access
sample = lug[0]
sample["audio"]["array"], sample["audio"]["sampling_rate"], sample["text"]
```

Access requires a Hugging Face account with permission to this repository; authenticate with
`hf auth login` (or set `HF_TOKEN`) before loading.

## Configurations

| Config | Contents |
| --- | --- |
| `all` (default) | All 20,213 rows |
| `<language code>` e.g. `lug`, `swa`, `yor` | All subsets of one language (51 configs) |
| `<code>_<source>` e.g. `lug_salt`, `hau_fleurs` | One source subset (110 configs) |

Every configuration has a single `test` split.

## Data fields

| Field | Type | Description |
| --- | --- | --- |
| `id` | string | Utterance id, carried over from Sunbird/speech |
| `audio` | Audio | Original encoded audio bytes (OGG/OPUS), decoded and resampled to 16 kHz when accessed |
| `text` | string | Reference transcript, unnormalized, as in the source |
| `duration` | float64 | Clip duration in seconds |
| `language` | string | ISO 639-3 code (the language token forced at decoding time) |
| `language_name` | string | English language name |
| `subset` | string | Source subset name, `<code>_<source>` |
| `source` | string | Name of the upstream corpus |

## Dataset construction

Rows were selected from the held-out **test** splits of `Sunbird/speech` (revision `4edec52`), a
harmonised collection of public and community-collected African speech corpora (every subset
has its own train/dev/test split), replaying the evaluation pipeline exactly:

1. For each of the 110 subsets of the 51 languages, take the **first 200 rows** of
   the `test` split in storage order (`test[:200]`, no shuffling).
2. Drop clips longer than **30 s**, comparing durations rounded to 10 ms
   (698 clips). The rounding keeps one boundary clip, `nextvoices_sot_8b28b599`
   (30.004 s), which is scored in the published SunflowerASR results.
3. Drop clips whose reference transcript is empty after text normalisation (3 clips), since
   they cannot be scored.

52 of the 110 subsets contribute the full 200 clips; the rest have smaller test splits or lost
clips to the length filter. Audio and transcripts are otherwise unchanged.

## Statistics

### By language

| Language | Code | Subsets | Examples | Hours | Mean dur. (s) | Sources |
| --- | --- | ---: | ---: | ---: | ---: | --- |
| Acholi | `ach` | 2 | 270 | 1.13 | 15.1 | Google WAXAL; Sunbird SALT |
| Afrikaans | `afr` | 4 | 729 | 3.27 | 16.1 | ASR Africa Data Efficiency Benchmark; Afrikaans-30s; Google FLEURS; Mozilla Common Voice |
| Akan | `aka` | 1 | 200 | 1.08 | 19.5 | Google WAXAL |
| Amharic | `amh` | 5 | 1,000 | 2.99 | 10.8 | ASR Africa Data Efficiency Benchmark; Google WAXAL; KYAGABA; Mozilla Common Voice; Shunya Labs |
| Ateso | `teo` | 1 | 98 | 0.18 | 6.5 | Sunbird SALT |
| Bambara | `bam` | 3 | 600 | 0.48 | 2.9 | ASR Africa Data Efficiency Benchmark; RobotsMali Bambara ASR |
| Bemba | `bem` | 2 | 400 | 0.87 | 7.9 | ASR Africa Data Efficiency Benchmark; BembaSpeech |
| Berber | `ber` | 1 | 200 | 0.12 | 2.1 | TutlaytAI Amazigh ASR |
| Chichewa | `nya` | 2 | 399 | 0.99 | 8.9 | Google FLEURS; michsethowusu |
| Dagaare | `dga` | 1 | 200 | 1.09 | 19.6 | Google WAXAL |
| Dagbani | `dag` | 2 | 400 | 1.35 | 12.1 | Google WAXAL; Mozilla Common Voice |
| English | `eng` | 2 | 295 | 0.58 | 7.0 | AfriSpeech-200 (Intron Health); Sunbird SALT |
| Ewe | `ewe` | 2 | 400 | 2.17 | 19.6 | ASR Africa Data Efficiency Benchmark; Google WAXAL |
| French | `fra` | 1 | 200 | 0.13 | 2.4 | African-Accented French |
| Fulani | `ful` | 3 | 594 | 2.55 | 15.5 | ASR Africa Data Efficiency Benchmark; Google FLEURS; Google WAXAL |
| Hausa | `hau` | 6 | 1,130 | 2.19 | 7.0 | ASR Africa Data Efficiency Benchmark; African Voices; CLEAR Global; Google FLEURS; Mozilla Common Voice; NaijaVoices |
| Igbo | `ibo` | 5 | 860 | 1.79 | 7.5 | ASR Africa Data Efficiency Benchmark; African Voices; Google FLEURS; Mozilla Common Voice; NaijaVoices |
| Ikposo | `kpo` | 1 | 200 | 1.13 | 20.3 | Google WAXAL |
| Kabyle | `kab` | 1 | 200 | 0.24 | 4.3 | Mozilla Common Voice |
| Kalenjin | `kln` | 2 | 400 | 0.77 | 6.9 | African Next Voices (Kenya); Mozilla Common Voice |
| Kanuri | `kau` | 1 | 200 | 0.40 | 7.1 | CLEAR Global |
| Kikuyu | `kik` | 1 | 199 | 0.34 | 6.1 | African Next Voices (Kenya) |
| Kinyarwanda | `kin` | 2 | 400 | 0.61 | 5.5 | ASR Africa Data Efficiency Benchmark; Mozilla Common Voice |
| Kwamba | `rwm` | 1 | 199 | 1.24 | 22.5 | Mozilla Common Voice |
| Lendu | `led` | 1 | 199 | 0.97 | 17.5 | Mozilla Common Voice |
| Lingala | `lin` | 4 | 767 | 3.89 | 18.3 | Google FLEURS; Google WAXAL; KasuleTrevor Lingala; Shunya Labs |
| Luganda | `lug` | 6 | 950 | 3.41 | 12.9 | ASR Africa Data Efficiency Benchmark; Google FLEURS; Google WAXAL; Makerere Radio Speech; Mozilla Common Voice; Sunbird SALT |
| Lugbara | `lgg` | 1 | 96 | 0.22 | 8.3 | Sunbird SALT |
| Luhya | `luy` | 1 | 200 | 0.52 | 9.4 | Digital Divide Data |
| Lumasaba | `myx` | 1 | 180 | 0.98 | 19.5 | Google WAXAL |
| Luo | `luo` | 3 | 596 | 1.45 | 8.7 | African Next Voices (Kenya); Google FLEURS; Mozilla Common Voice |
| Lusoga | `xog` | 1 | 177 | 1.04 | 21.2 | Google WAXAL |
| Malagasy | `mlg` | 1 | 199 | 1.00 | 18.1 | Google WAXAL |
| Ndebele | `nbl` | 1 | 144 | 0.64 | 16.1 | African Next Voices (Southern Africa) |
| Nigerian Pidgin | `pcm` | 2 | 397 | 0.71 | 6.4 | African Voices; Mozilla Common Voice |
| Oromo | `orm` | 3 | 439 | 1.42 | 11.6 | ASR Africa Data Efficiency Benchmark; Google FLEURS; Google WAXAL |
| Rukiga | `cgg` | 1 | 200 | 0.60 | 10.9 | Mozilla Common Voice |
| Rukonjo | `koo` | 1 | 200 | 0.96 | 17.3 | Mozilla Common Voice |
| Runyankole | `nyn` | 2 | 280 | 1.20 | 15.4 | Google WAXAL; Sunbird SALT |
| Ruruuli | `ruc` | 1 | 170 | 0.78 | 16.5 | Mozilla Common Voice |
| Rutooro | `ttj` | 1 | 199 | 1.02 | 18.4 | Mozilla Common Voice |
| Shona | `sna` | 3 | 594 | 3.05 | 18.5 | ASR Africa Data Efficiency Benchmark; Google FLEURS; Google WAXAL |
| Somali | `som` | 3 | 596 | 1.07 | 6.5 | African Next Voices (Kenya); Google FLEURS; Soomali ASR |
| Sotho | `sot` | 2 | 321 | 1.44 | 16.1 | African Next Voices (Southern Africa); Google FLEURS |
| Swahili | `swa` | 2 | 400 | 1.12 | 10.1 | Google FLEURS; Mozilla Common Voice |
| Thur | `lth` | 1 | 167 | 0.67 | 14.5 | Mozilla Common Voice |
| Tswana | `tsn` | 2 | 369 | 0.78 | 7.6 | African Next Voices (Southern Africa); Mozilla Common Voice |
| Wolof | `wol` | 3 | 571 | 1.83 | 11.5 | ASR Africa Data Efficiency Benchmark; Google FLEURS; Kallaama |
| Xhosa | `xho` | 3 | 527 | 2.02 | 13.8 | ASR Africa Data Efficiency Benchmark; African Next Voices (Southern Africa); Google FLEURS |
| Yoruba | `yor` | 5 | 995 | 2.03 | 7.4 | ASR Africa Data Efficiency Benchmark; African Voices; Google FLEURS; Mozilla Common Voice; NaijaVoices |
| Zulu | `zul` | 3 | 507 | 2.31 | 16.4 | ASR Africa Data Efficiency Benchmark; African Next Voices (Southern Africa); Google FLEURS |
| **Total** |  | 110 | **20,213** | **64.82** | 11.5 | 24 sources |

### By source dataset

| Source dataset | Languages | Subsets | Examples | Hours | License (upstream) |
| --- | --- | ---: | ---: | ---: | --- |
| [Mozilla Common Voice](https://commonvoice.mozilla.org) | Afrikaans, Amharic, Dagbani, Hausa, Igbo, Kabyle, Kalenjin, Kinyarwanda, Kwamba, Lendu, Luganda, Luo, Nigerian Pidgin, Rukiga, Rukonjo, Ruruuli, Rutooro, Swahili, Thur, Tswana, Yoruba | 21 | 3,952 | 10.19 | CC0-1.0 |
| [ASR Africa Data Efficiency Benchmark](https://huggingface.co/datasets/asr-africa/ASRAfricaDataEfficiencyBenchmark) | Afrikaans, Amharic, Bambara, Bemba, Ewe, Fulani, Hausa, Igbo, Kinyarwanda, Luganda, Oromo, Shona, Wolof, Xhosa, Yoruba, Zulu | 16 | 3,166 | 9.42 | See source |
| [Google FLEURS](https://huggingface.co/datasets/google/fleurs) | Afrikaans, Chichewa, Fulani, Hausa, Igbo, Lingala, Luganda, Luo, Oromo, Shona, Somali, Sotho, Swahili, Wolof, Xhosa, Yoruba, Zulu | 17 | 3,128 | 13.16 | CC-BY-4.0 |
| [Google WAXAL](https://huggingface.co/datasets/google/WaxalNLP) | Acholi, Akan, Amharic, Dagaare, Dagbani, Ewe, Fulani, Ikposo, Lingala, Luganda, Lumasaba, Lusoga, Malagasy, Oromo, Runyankole, Shona | 16 | 3,053 | 16.35 | CC-BY-4.0 / CC-BY-SA-4.0 |
| [African Next Voices (Kenya)](https://huggingface.co/datasets/dsfsi-anv/za-african-next-voices) | Kalenjin, Kikuyu, Luo, Somali | 4 | 797 | 1.45 | See source |
| [African Voices](https://africanvoices.io/download) | Hausa, Igbo, Nigerian Pidgin, Yoruba | 4 | 741 | 1.59 | See source |
| [African Next Voices (Southern Africa)](https://huggingface.co/datasets/dsfsi-anv/za-african-next-voices) | Ndebele, Sotho, Tswana, Xhosa, Zulu | 5 | 709 | 3.02 | CC-BY-4.0 |
| [NaijaVoices](https://huggingface.co/datasets/naijavoices/naijavoices-dataset) | Hausa, Igbo, Yoruba | 3 | 600 | 0.60 | CC-BY-NC-SA-4.0 |
| [Sunbird SALT](https://huggingface.co/datasets/Sunbird/salt) | Acholi, Ateso, English, Luganda, Lugbara, Runyankole | 6 | 584 | 1.02 | CC-BY-SA-4.0 |
| [RobotsMali Bambara ASR](https://huggingface.co/datasets/RobotsMali/bam-asr-early) | Bambara | 2 | 400 | 0.30 | See source |
| [CLEAR Global](https://huggingface.co/CLEAR-Global) | Hausa, Kanuri | 2 | 400 | 0.80 | See source |
| [Shunya Labs](https://huggingface.co/shunyalabs) | Amharic, Lingala | 2 | 387 | 1.59 | See source |
| [Digital Divide Data](https://datacollective.mozillafoundation.org/datasets/cmkh2stj6004mmj0751rn8vq6) | Luhya | 1 | 200 | 0.52 | See source |
| [BembaSpeech](https://huggingface.co/csikasote) | Bemba | 1 | 200 | 0.44 | See source |
| [African-Accented French](https://huggingface.co/datasets/gigant/african_accented_french) | French | 1 | 200 | 0.13 | CC |
| [Afrikaans-30s](https://huggingface.co/datasets/andreoosthuizen/afrikaans-30s) | Afrikaans | 1 | 200 | 1.67 | CC-BY-4.0 |
| [TutlaytAI Amazigh ASR](https://huggingface.co/TutlaytAI) | Berber | 1 | 200 | 0.12 | See source |
| [Soomali ASR](https://huggingface.co/datasets/skydheere/soomali-asr-dataset) | Somali | 1 | 200 | 0.09 | CC-BY-4.0 |
| [KasuleTrevor Lingala](https://huggingface.co/KasuleTrevor) | Lingala | 1 | 200 | 1.02 | See source |
| [KYAGABA](https://huggingface.co/KYAGABA) | Amharic | 1 | 200 | 0.40 | See source |
| [michsethowusu](https://huggingface.co/michsethowusu) | Chichewa | 1 | 200 | 0.09 | See source |
| [AfriSpeech-200 (Intron Health)](https://huggingface.co/datasets/intronhealth/afrispeech-200) | English | 1 | 199 | 0.45 | CC-BY-NC-SA-4.0 |
| [Kallaama](https://huggingface.co/datasets/yigagilbert/kallaama-trs-dataset-19hr) | Wolof | 1 | 197 | 0.20 | See source |
| [Makerere Radio Speech](https://huggingface.co/datasets/allandclive/MakerereRadioSpeech_20Hrs) | Luganda | 1 | 100 | 0.19 | See source |

### By subset

<details>
<summary>All 110 subsets (click to expand)</summary>

| Subset | Language | Source | Examples | Hours | Mean dur. (s) | Max dur. (s) | Dropped >30 s | Dropped empty text |
| --- | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: |
| `ach_salt` | Acholi | Sunbird SALT | 96 | 0.16 | 5.9 | 17.9 | 0 | 0 |
| `ach_waxal` | Acholi | Google WAXAL | 174 | 0.97 | 20.1 | 29.9 | 26 | 0 |
| `afr_afrikaans30s` | Afrikaans | Afrikaans-30s | 200 | 1.67 | 30.0 | 30.0 | 0 | 0 |
| `afr_commonvoice` | Afrikaans | Mozilla Common Voice | 129 | 0.23 | 6.3 | 14.0 | 0 | 0 |
| `afr_fleurs` | Afrikaans | Google FLEURS | 200 | 0.69 | 12.4 | 29.6 | 0 | 0 |
| `afr_makbenchmark` | Afrikaans | ASR Africa Data Efficiency Benchmark | 200 | 0.69 | 12.3 | 29.6 | 0 | 0 |
| `aka_waxal` | Akan | Google WAXAL | 200 | 1.08 | 19.5 | 28.8 | 0 | 0 |
| `amh_commonvoice` | Amharic | Mozilla Common Voice | 200 | 0.36 | 6.4 | 10.5 | 0 | 0 |
| `amh_kyagaba` | Amharic | KYAGABA | 200 | 0.40 | 7.2 | 17.0 | 0 | 0 |
| `amh_makbenchmark` | Amharic | ASR Africa Data Efficiency Benchmark | 200 | 0.62 | 11.1 | 18.7 | 0 | 0 |
| `amh_shunyalabs` | Amharic | Shunya Labs | 200 | 0.64 | 11.4 | 28.9 | 0 | 0 |
| `amh_waxal` | Amharic | Google WAXAL | 200 | 0.98 | 17.7 | 26.1 | 0 | 0 |
| `bam_makbenchmark` | Bambara | ASR Africa Data Efficiency Benchmark | 200 | 0.18 | 3.2 | 10.2 | 0 | 0 |
| `bam_robotsbambari` | Bambara | RobotsMali Bambara ASR | 200 | 0.19 | 3.4 | 12.2 | 0 | 0 |
| `bam_robotsmali` | Bambara | RobotsMali Bambara ASR | 200 | 0.12 | 2.1 | 7.9 | 0 | 0 |
| `bem_csikasote` | Bemba | BembaSpeech | 200 | 0.44 | 7.9 | 17.1 | 0 | 0 |
| `bem_makbenchmark` | Bemba | ASR Africa Data Efficiency Benchmark | 200 | 0.44 | 7.9 | 16.5 | 0 | 0 |
| `ber_tutlay` | Berber | TutlaytAI Amazigh ASR | 200 | 0.12 | 2.1 | 4.7 | 0 | 0 |
| `cgg_commonvoice` | Rukiga | Mozilla Common Voice | 200 | 0.60 | 10.9 | 27.1 | 0 | 0 |
| `dag_commonvoice` | Dagbani | Mozilla Common Voice | 200 | 0.26 | 4.6 | 11.4 | 0 | 0 |
| `dag_waxal` | Dagbani | Google WAXAL | 200 | 1.09 | 19.7 | 28.5 | 0 | 0 |
| `dga_waxal` | Dagaare | Google WAXAL | 200 | 1.09 | 19.6 | 30.0 | 0 | 0 |
| `eng_intronhealth` | English | AfriSpeech-200 (Intron Health) | 199 | 0.45 | 8.1 | 23.8 | 0 | 1 |
| `eng_salt` | English | Sunbird SALT | 96 | 0.13 | 4.9 | 9.4 | 0 | 0 |
| `ewe_makbenchmark` | Ewe | ASR Africa Data Efficiency Benchmark | 200 | 1.10 | 19.9 | 28.7 | 0 | 0 |
| `ewe_waxal` | Ewe | Google WAXAL | 200 | 1.07 | 19.3 | 29.8 | 0 | 0 |
| `fra_gigant` | French | African-Accented French | 200 | 0.13 | 2.4 | 12.0 | 0 | 0 |
| `ful_fleurs` | Fulani | Google FLEURS | 198 | 0.75 | 13.6 | 29.3 | 2 | 0 |
| `ful_makbenchmark` | Fulani | ASR Africa Data Efficiency Benchmark | 198 | 0.75 | 13.6 | 29.3 | 2 | 0 |
| `ful_waxal` | Fulani | Google WAXAL | 198 | 1.05 | 19.2 | 29.1 | 2 | 0 |
| `hau_africanvoices` | Hausa | African Voices | 154 | 0.29 | 6.9 | 11.7 | 46 | 0 |
| `hau_clearglobal` | Hausa | CLEAR Global | 200 | 0.40 | 7.3 | 16.6 | 0 | 0 |
| `hau_commonvoice` | Hausa | Mozilla Common Voice | 200 | 0.28 | 5.0 | 9.8 | 0 | 0 |
| `hau_fleurs` | Hausa | Google FLEURS | 176 | 0.87 | 17.7 | 30.0 | 24 | 0 |
| `hau_makbenchmark` | Hausa | ASR Africa Data Efficiency Benchmark | 200 | 0.17 | 3.0 | 7.4 | 0 | 0 |
| `hau_naijavoices` | Hausa | NaijaVoices | 200 | 0.17 | 3.1 | 11.7 | 0 | 0 |
| `ibo_africanvoices` | Igbo | African Voices | 192 | 0.45 | 8.4 | 16.6 | 8 | 0 |
| `ibo_commonvoice` | Igbo | Mozilla Common Voice | 89 | 0.14 | 5.6 | 10.3 | 0 | 0 |
| `ibo_fleurs` | Igbo | Google FLEURS | 179 | 0.76 | 15.3 | 30.0 | 21 | 0 |
| `ibo_makbenchmark` | Igbo | ASR Africa Data Efficiency Benchmark | 200 | 0.21 | 3.8 | 9.7 | 0 | 0 |
| `ibo_naijavoices` | Igbo | NaijaVoices | 200 | 0.23 | 4.1 | 10.7 | 0 | 0 |
| `kab_commonvoice` | Kabyle | Mozilla Common Voice | 200 | 0.24 | 4.3 | 10.3 | 0 | 0 |
| `kau_clearglobal` | Kanuri | CLEAR Global | 200 | 0.40 | 7.1 | 19.1 | 0 | 0 |
| `kik_anvkekikuyu` | Kikuyu | African Next Voices (Kenya) | 199 | 0.34 | 6.1 | 26.2 | 1 | 0 |
| `kin_commonvoice` | Kinyarwanda | Mozilla Common Voice | 200 | 0.30 | 5.3 | 10.5 | 0 | 0 |
| `kin_makbenchmark` | Kinyarwanda | ASR Africa Data Efficiency Benchmark | 200 | 0.31 | 5.6 | 9.9 | 0 | 0 |
| `kln_ankekalenjin` | Kalenjin | African Next Voices (Kenya) | 200 | 0.43 | 7.7 | 25.5 | 0 | 0 |
| `kln_commonvoice` | Kalenjin | Mozilla Common Voice | 200 | 0.35 | 6.2 | 15.4 | 0 | 0 |
| `koo_commonvoice` | Rukonjo | Mozilla Common Voice | 200 | 0.96 | 17.3 | 26.0 | 0 | 0 |
| `kpo_waxal` | Ikposo | Google WAXAL | 200 | 1.13 | 20.3 | 29.9 | 0 | 0 |
| `led_commonvoice` | Lendu | Mozilla Common Voice | 199 | 0.97 | 17.5 | 25.7 | 1 | 0 |
| `lgg_salt` | Lugbara | Sunbird SALT | 96 | 0.22 | 8.3 | 16.4 | 0 | 0 |
| `lin_fleurs` | Lingala | Google FLEURS | 187 | 0.95 | 18.4 | 29.9 | 13 | 0 |
| `lin_kasuletrev` | Lingala | KasuleTrevor Lingala | 200 | 1.02 | 18.3 | 26.8 | 0 | 0 |
| `lin_shunyalabs` | Lingala | Shunya Labs | 187 | 0.95 | 18.4 | 29.9 | 13 | 0 |
| `lin_waxal` | Lingala | Google WAXAL | 193 | 0.97 | 18.0 | 29.5 | 7 | 0 |
| `lth_commonvoice` | Thur | Mozilla Common Voice | 167 | 0.67 | 14.5 | 27.6 | 4 | 0 |
| `lug_commonvoice` | Luganda | Mozilla Common Voice | 200 | 0.34 | 6.1 | 10.6 | 0 | 0 |
| `lug_fleurs` | Luganda | Google FLEURS | 196 | 0.92 | 16.9 | 29.4 | 4 | 0 |
| `lug_makbenchmark` | Luganda | ASR Africa Data Efficiency Benchmark | 197 | 0.91 | 16.6 | 29.9 | 3 | 0 |
| `lug_makerereradio` | Luganda | Makerere Radio Speech | 100 | 0.19 | 6.8 | 15.8 | 0 | 0 |
| `lug_salt` | Luganda | Sunbird SALT | 99 | 0.16 | 5.9 | 11.8 | 0 | 0 |
| `lug_waxal` | Luganda | Google WAXAL | 158 | 0.89 | 20.3 | 29.5 | 42 | 0 |
| `luo_anvkeluo` | Luo | African Next Voices (Kenya) | 198 | 0.44 | 8.1 | 29.7 | 1 | 1 |
| `luo_commonvoice` | Luo | Mozilla Common Voice | 200 | 0.25 | 4.6 | 20.5 | 0 | 0 |
| `luo_fleurs` | Luo | Google FLEURS | 198 | 0.75 | 13.6 | 29.2 | 2 | 0 |
| `luy_digitaldivide` | Luhya | Digital Divide Data | 200 | 0.52 | 9.4 | 25.2 | 0 | 0 |
| `mlg_waxal` | Malagasy | Google WAXAL | 199 | 1.00 | 18.1 | 29.3 | 1 | 0 |
| `myx_waxal` | Lumasaba | Google WAXAL | 180 | 0.98 | 19.5 | 30.0 | 19 | 1 |
| `nbl_nextvoices` | Ndebele | African Next Voices (Southern Africa) | 144 | 0.64 | 16.1 | 29.4 | 56 | 0 |
| `nya_fleurs` | Chichewa | Google FLEURS | 199 | 0.90 | 16.2 | 29.5 | 1 | 0 |
| `nya_michsethowusu` | Chichewa | michsethowusu | 200 | 0.09 | 1.7 | 4.4 | 0 | 0 |
| `nyn_salt` | Runyankole | Sunbird SALT | 99 | 0.17 | 6.2 | 11.6 | 0 | 0 |
| `nyn_waxal` | Runyankole | Google WAXAL | 181 | 1.03 | 20.5 | 29.5 | 19 | 0 |
| `orm_fleurs` | Oromo | Google FLEURS | 41 | 0.13 | 11.4 | 25.9 | 0 | 0 |
| `orm_makbenchmark` | Oromo | ASR Africa Data Efficiency Benchmark | 200 | 0.41 | 7.4 | 14.2 | 0 | 0 |
| `orm_waxal` | Oromo | Google WAXAL | 198 | 0.88 | 16.0 | 23.9 | 2 | 0 |
| `pcm_africanvoices` | Nigerian Pidgin | African Voices | 197 | 0.42 | 7.6 | 19.9 | 3 | 0 |
| `pcm_commonvoice` | Nigerian Pidgin | Mozilla Common Voice | 200 | 0.29 | 5.2 | 9.9 | 0 | 0 |
| `ruc_commonvoice` | Ruruuli | Mozilla Common Voice | 170 | 0.78 | 16.5 | 29.7 | 30 | 0 |
| `rwm_commonvoice` | Kwamba | Mozilla Common Voice | 199 | 1.24 | 22.5 | 29.0 | 1 | 0 |
| `sna_fleurs` | Shona | Google FLEURS | 200 | 0.82 | 14.8 | 27.7 | 0 | 0 |
| `sna_makbenchmark` | Shona | ASR Africa Data Efficiency Benchmark | 199 | 1.13 | 20.4 | 29.9 | 1 | 0 |
| `sna_waxal` | Shona | Google WAXAL | 195 | 1.10 | 20.3 | 29.5 | 5 | 0 |
| `som_anvkesomali` | Somali | African Next Voices (Kenya) | 200 | 0.24 | 4.4 | 14.1 | 0 | 0 |
| `som_fleurs` | Somali | Google FLEURS | 196 | 0.73 | 13.4 | 26.4 | 4 | 0 |
| `som_skydheere` | Somali | Soomali ASR | 200 | 0.09 | 1.7 | 6.3 | 0 | 0 |
| `sot_fleurs` | Sotho | Google FLEURS | 187 | 0.90 | 17.3 | 29.9 | 13 | 0 |
| `sot_nextvoices` | Sotho | African Next Voices (Southern Africa) | 134 | 0.54 | 14.4 | 30.0 | 66 | 0 |
| `swa_commonvoice` | Swahili | Mozilla Common Voice | 200 | 0.33 | 5.9 | 10.2 | 0 | 0 |
| `swa_fleurs` | Swahili | Google FLEURS | 200 | 0.79 | 14.2 | 28.4 | 0 | 0 |
| `teo_salt` | Ateso | Sunbird SALT | 98 | 0.18 | 6.5 | 13.7 | 0 | 0 |
| `tsn_commonvoice` | Tswana | Mozilla Common Voice | 200 | 0.24 | 4.3 | 9.7 | 0 | 0 |
| `tsn_nextvoices` | Tswana | African Next Voices (Southern Africa) | 169 | 0.55 | 11.6 | 29.3 | 31 | 0 |
| `ttj_commonvoice` | Rutooro | Mozilla Common Voice | 199 | 1.02 | 18.4 | 28.5 | 1 | 0 |
| `wol_fleurs` | Wolof | Google FLEURS | 188 | 0.84 | 16.2 | 28.2 | 12 | 0 |
| `wol_kallama` | Wolof | Kallaama | 197 | 0.20 | 3.6 | 28.1 | 3 | 0 |
| `wol_makbenchmark` | Wolof | ASR Africa Data Efficiency Benchmark | 186 | 0.79 | 15.3 | 28.2 | 14 | 0 |
| `xho_fleurs` | Xhosa | Google FLEURS | 198 | 0.70 | 12.7 | 29.4 | 2 | 0 |
| `xho_makbenchmark` | Xhosa | ASR Africa Data Efficiency Benchmark | 197 | 0.70 | 12.8 | 26.2 | 3 | 0 |
| `xho_nextvoices` | Xhosa | African Next Voices (Southern Africa) | 132 | 0.62 | 17.0 | 30.0 | 68 | 0 |
| `xog_waxal` | Lusoga | Google WAXAL | 177 | 1.04 | 21.2 | 29.7 | 23 | 0 |
| `yor_africanvoices` | Yoruba | African Voices | 198 | 0.43 | 7.8 | 16.8 | 2 | 0 |
| `yor_commonvoice` | Yoruba | Mozilla Common Voice | 200 | 0.36 | 6.5 | 10.3 | 0 | 0 |
| `yor_fleurs` | Yoruba | Google FLEURS | 197 | 0.84 | 15.4 | 29.0 | 3 | 0 |
| `yor_makbenchmark` | Yoruba | ASR Africa Data Efficiency Benchmark | 200 | 0.20 | 3.6 | 15.5 | 0 | 0 |
| `yor_naijavoices` | Yoruba | NaijaVoices | 200 | 0.20 | 3.6 | 9.4 | 0 | 0 |
| `zul_fleurs` | Zulu | Google FLEURS | 188 | 0.82 | 15.6 | 29.5 | 12 | 0 |
| `zul_makbenchmark` | Zulu | ASR Africa Data Efficiency Benchmark | 189 | 0.82 | 15.7 | 29.5 | 11 | 0 |
| `zul_nextvoices` | Zulu | African Next Voices (Southern Africa) | 130 | 0.67 | 18.5 | 29.9 | 70 | 0 |

</details>

## Evaluation protocol

Results reported for [`Sunbird/asr-whisper-51-african-languages`](https://huggingface.co/Sunbird/asr-whisper-51-african-languages) on this benchmark use:

- **Language forcing:** the decoder is given the language of each clip (`language` column).
- **Text normalisation:** Whisper's `BasicTextNormalizer`
  (`transformers.models.whisper.english_normalizer`), applied to both reference and hypothesis,
  lower-cases and strips punctuation and symbols.
- **Metrics:** corpus-level WER and CER (total edits over total reference words/characters,
  computed with `jiwer`), reported per subset, per language (pooling all of a language's
  subsets) and overall (pooling every clip). The pooled overall number is weighted towards
  languages with more clips; averaging the per-language scores instead (macro average) weights
  every language equally.

To reproduce the numbers exactly, apply the same normalisation and aggregate at corpus level
rather than averaging per-utterance scores.

## Sources and licensing

The clips are redistributed from the corpora in the [source table](#by-source-dataset) above; the
source of each clip is in its `source` column. **Each clip remains subject to the license and
terms of its upstream corpus**, several of which are non-commercial (NC) or share-alike (SA). The
license column shows what the upstream Hugging Face repository declares where it declares one;
check the source for everything else, and before any commercial use.

For more on the corpora, see the
[training datasets section](https://huggingface.co/Sunbird/asr-whisper-51-african-languages#training-datasets) of the model
card. The test clips here come from the held-out test splits of those same corpora.

## Considerations and limitations

- **In-domain by construction.** The clips come from the test splits of the same corpora whose
  train splits were used to train SunflowerASR, so scores reflect in-domain performance and may
  be optimistic for noisier or more spontaneous speech. Whether speakers are disjoint across
  splits depends on how each corpus was partitioned.
- **Uneven coverage.** Languages range from 96 to 1,130 clips and from 1 to
  6 source corpora, so per-language confidence intervals differ widely.
- **Storage-order sampling.** The first 200 rows of a test split may come from a small number of
  speakers or sessions if the source groups rows that way.
- **Duplicated Lingala clips.** `lin_shunyalabs` and `lin_fleurs` contain the same 187 recordings
  (identical transcripts, and waveforms that match once decoded; only the encoding differs), so
  Lingala's pooled metrics count them twice. Both are kept so the benchmark matches the published
  results; drop one of the two subsets for a de-duplicated Lingala score.
- **`id` is not unique.** 8 ids in the Common Voice subsets for Rukiga, Rukonjo, Lendu, Thur and
  Ruruuli are each shared by 4 different recordings, so identify rows by position rather than by
  `id` alone.
- **Transcription conventions differ between sources** (for example in casing, punctuation and how
  numbers are written) and are not harmonised beyond the normalisation above.

## Citation

If you use this benchmark, please cite the SunflowerASR model and the upstream corpora for
the languages you report.

```bibtex
@misc{sunbird_speech_benchmark_2026,
  title        = {Sunbird Speech Benchmark: a multilingual ASR test set for 51 African languages},
  author       = {Sunbird AI},
  year         = {2026},
  howpublished = {\url{https://huggingface.co/datasets/Sunbird/speech-benchmark}}
}
```