README.md

metadata

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 (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

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	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	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	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	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)	Kalenjin, Kikuyu, Luo, Somali	4	797	1.45	See source
African Voices	Hausa, Igbo, Nigerian Pidgin, Yoruba	4	741	1.59	See source
African Next Voices (Southern Africa)	Ndebele, Sotho, Tswana, Xhosa, Zulu	5	709	3.02	CC-BY-4.0
NaijaVoices	Hausa, Igbo, Yoruba	3	600	0.60	CC-BY-NC-SA-4.0
Sunbird SALT	Acholi, Ateso, English, Luganda, Lugbara, Runyankole	6	584	1.02	CC-BY-SA-4.0
RobotsMali Bambara ASR	Bambara	2	400	0.30	See source
CLEAR Global	Hausa, Kanuri	2	400	0.80	See source
Shunya Labs	Amharic, Lingala	2	387	1.59	See source
Digital Divide Data	Luhya	1	200	0.52	See source
BembaSpeech	Bemba	1	200	0.44	See source
African-Accented French	French	1	200	0.13	CC
Afrikaans-30s	Afrikaans	1	200	1.67	CC-BY-4.0
TutlaytAI Amazigh ASR	Berber	1	200	0.12	See source
Soomali ASR	Somali	1	200	0.09	CC-BY-4.0
KasuleTrevor Lingala	Lingala	1	200	1.02	See source
KYAGABA	Amharic	1	200	0.40	See source
michsethowusu	Chichewa	1	200	0.09	See source
AfriSpeech-200 (Intron Health)	English	1	199	0.45	CC-BY-NC-SA-4.0
Kallaama	Wolof	1	197	0.20	See source
Makerere Radio Speech	Luganda	1	100	0.19	See source

By subset

All 110 subsets (click to expand)

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

Evaluation protocol

Results reported for 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 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 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.

@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}}
}