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benchmark_id
stringlengths
44
47
audio
audioduration (s)
1.02
9.58
text
stringclasses
130 values
duration_s
float32
1.02
9.58
lang_iso3
stringclasses
1 value
lang_name
stringclasses
1 value
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1901
Ye be hyia bio
5.55
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1425
Na biribiara dwoi
1.67
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx349
Yɛ wɔ
5.07
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx726
Woforo dua pa a na ye pia wo
6.84
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2219
Mehu mayɛ ewie
5.47
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1150
Saa
5.41
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1463
Woretɔ agu number bɛn so
6.52
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx76
Emu biara
5.02
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx654
Me ho mfa me
5.23
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx214
Wɔn ti
1.23
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2691
Tow nnwom
4.54
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx958
Dɛɛbi dɛɛbi me pɛsɛ me tɔ
4.18
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx196
Mame bebree
6.3
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx283
Abofra yi
7.16
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1328
Eyinom nyinaa yɛ wodea
6.29
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1057
Nti ɔtɔɔ afe fa bi
6.7
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx944
Me pɛsɛ mi tɔ credit 10 cedis
6.2
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx681
Tikoro nnkɔ agyina
2.33
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx864
Efi sɛ
6.36
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx783
ɔkɔm de me
5.53
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2009
Nantew yiye
3.22
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1386
Hena akonwa
6.26
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx169
agu 054
8.72
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1504
Nea edi kan
2.4
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2297
Abofra no to nwom
4.81
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1910
Ye be hyia bio
6.33
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2848
Kɔɔ dua bi akyi
8.16
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1421
Na biribiara dwoi
6.9
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1780
Daabi
3.17
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx322
Mepawokyɛw Yiw
1.91
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx222
Ngo a aguu asuafo no ho
2.94
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2115
ɛye
5.39
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1913
Tew so ma me
6.85
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1583
ɛno akyi no
2.25
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx446
mmere nni hɔ
4.38
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx199
Wɔn ti
1.62
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx888
Yiw
5.17
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx772
ɛyɛ fɛ
1.61
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2257
Esian sɛ
5.12
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2610
Okuu adubɔfo
6.34
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2545
Woadi Ńkɔmmɔ mprɛnsa
3.67
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx71
Emu biara
5.79
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2046
Medɔ wo
6.42
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1949
Wo pɛ dɛn
1.03
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1280
Me ho ye paa ara
7.62
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx665
Me ho mfa me
7.41
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2028
ɔkɔtɔ nnwo anomaa
4.9
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx765
ɛyɛ fɛ
1.7
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2893
Ɛsow aba pii
5.44
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1287
Me ho ye paa ara
1.9
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx188
Mame bebree
5.05
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx477
Wote brɔfo
5.31
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2646
Ne yere
1.02
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1131
Mepaw’ kyɛw Yiw
9.2
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2838
Tuu no
1.84
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2490
Akwaaba
6.61
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1965
Mayera
6.05
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1140
Mepaw’ kyɛw Yiw
6.82
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx664
Me ho mfa me
6.44
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1435
Woanyin sen me
6.37
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1193
Due, manhyɛ da
6.44
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2699
Tow nnwom
5.45
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx775
ɛyɛ fɛ
4.73
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx943
Me pɛsɛ mi tɔ credit 10 cedis
4.66
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx801
Osu kɔm de me
2.8
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1307
Yiw
5.43
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2359
Mepawokyɛw ma sesa madwene
5.43
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1891
To so ma me
6.27
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2611
Okuu adubɔfo
3.79
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1892
Ye be hyia bio
4.84
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1181
Mereyɛ credit transfer 10 cedis
4.3
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2643
Ne yere
3.13
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx758
ɛyɛ fɛ
3.28
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1229
Me ho ye paa
4.69
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1467
Woretɔ agu number bɛn so
2.45
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1201
Due, manhyɛ da
1.66
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx708
Mafe wo
5.37
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2354
Mepawokyɛw ma sesa madwene
5.56
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx672
Tikoro nnkɔ agyina
8.08
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2798
Dan mu
5.12
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1648
Awi no rehwehwɛ ahu
3.55
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx205
Wɔn ti
2.04
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx916
Nokware di tuo
6.26
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx856
Me credit aka ahe
7.36
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1086
Neho ayɛ fi paa
8.4
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx244
Ɛsoe pɛ
1.95
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1871
To so ma me
1.19
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx809
Osu kɔm de me
5.4
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1345
Hyɛ n'anim tee
6.36
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx1355
Hyɛ n'anim tee
7.03
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx191
Mame bebree
3.01
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx959
Dɛɛbi dɛɛbi me pɛsɛ me tɔ
7.5
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx779
ɔkɔm de me
6.07
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx363
Dum kanea no
3.69
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx781
ɔkɔm de me
2.92
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2465
Mepaw’kyɛw mɛ tɔ credit (spoken - informal)
5.91
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx480
Wote brɔfo
8
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2404
mɛtɔ credit 5 cedis
3.93
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx952
Dɛɛbi dɛɛbi me pɛsɛ me tɔ
7.38
Akuapim-twi
Akuapim-twi
test
Akuapim-twi_fin_speech_Akuapim-twi_test_idx2671
Adwoa Aboagye
1.5
Akuapim-twi
Akuapim-twi
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EMNLP 2025 Paper Official Website SimbaBench GitHub Repository Hugging Face Hugging Face Dataset

SibmaBench Data Release & Benchmarking

To evaluate your model on SimbaBench across all supported tasks (ASR, TTS, and SLID), simply load the corresponding configuration for the task and language you wish to benchmark.

Each task is organized by configuration name (e.g., asr_test_afr, tts_test_wol, slid_61_test). Loading a configuration provides the standardized evaluation split for that specific benchmark.

Example:

from datasets import load_dataset

data = load_dataset("UBC-NLP/SimbaBench_dataset", "asr_test_afr")
DatasetDict({
    test: Dataset({
        features: ['split', 'benchmark_id', 'audio', 'text', 'duration_s', 'lang_iso3', 'lang_name'],
        num_rows: 1000
    })
})
data['test'][0]
{'split': 'test',
 'benchmark_id': 'afr_Lwazi_afr_test_idx3889',
 'audio': {'path': None,
  'array': array([ 4.27246094e-04,  7.62939453e-04,  6.71386719e-04, ...,
         -3.05175781e-04, -2.13623047e-04, -6.10351562e-05]),
  'sampling_rate': 16000},
 'text': 'watter, verontwaardiging sou daar, in ons binneste gewees het?',
 'duration_s': 5.119999885559082,
 'lang_iso3': 'afr',
 'lang_name': 'Afrikaans'}

📌 ASR Evaluation Configurations

Config Name Language ISO # Samples # Hours
asr_test_Akuapim-twi Akuapim-twi Akuapim-twi 1,000 1.35
asr_test_Asante-twi Asante-twi Asante-twi 1,000 0.97
asr_test_afr Afrikaans afr 1,000 0.87
asr_test_amh Amharic amh 581 1.12
asr_test_bas Basaa bas 582 0.76
asr_test_bem Bemba bem 1,000 2.15
asr_test_dav Taita dav 878 1.17
asr_test_dyu Dyula dyu 59 0.10
asr_test_fat Fanti fat 1,000 1.38
asr_test_fon Fon fon 1,000 0.66
asr_test_fuc Pulaar fuc 100 0.10
asr_test_fuf Pular fuf 129 0.03
asr_test_gaa Ga gaa 1,000 1.52
asr_test_hau Hausa hau 681 0.89
asr_test_ibo Igbo ibo 5 0.01
asr_test_kab Kabyle kab 1,000 1.05
asr_test_kin Kinyarwanda kin 1,000 1.50
asr_test_kln Kalenjin kln 1,000 1.50
asr_test_loz Lozi loz 399 0.91
asr_test_lug Ganda lug 1,000 1.65
asr_test_luo Luo (Kenya and Tanzania) luo 1,000 1.31
asr_test_mlq Western Maninkakan mlq 182 0.04
asr_test_nbl South Ndebele nbl 1,000 1.12
asr_test_nso Northern Sotho nso 1,000 0.88
asr_test_nya Nyanja nya 428 1.31
asr_test_sot Southern Sotho sot 1,000 0.82
asr_test_srr Serer srr 899 2.84
asr_test_ssw Swati ssw 1,000 0.93
asr_test_sus Susu sus 210 0.05
asr_test_swa Swahili swa 1,000 1.23
asr_test_tig Tigre tig 185 0.33
asr_test_tir Tigrinya tir 7 0.01
asr_test_toi Tonga (Zambia) toi 463 1.47
asr_test_tsn Tswana tsn 1,000 0.82
asr_test_tso Tsonga tso 1,000 0.99
asr_test_twi Twi twi 12 0.02
asr_test_ven Venda ven 1,000 0.92
asr_test_wol Wolof wol 1,000 1.19
asr_test_xho Xhosa xho 1,000 0.92
asr_test_yor Yoruba yor 359 0.42
asr_test_zgh Standard Moroccan Tamazight zgh 197 0.22
asr_test_zul Zulu zul 1,000 1.10

📌 TTS Evaluation Configurations

Config Name Language ISO # Samples # Hours
tts_test_ewe Ewe ewe 66 0.29
tts_test_kin Kinyarwanda kin 1,053 1.30
tts_test_Asante-twi Asante-twi Asante-twi 64 0.18
tts_test_yor Yoruba yor 40 0.13
tts_test_wol Wolof wol 4,001 4.12
tts_test_hau Hausa hau 124 0.24
tts_test_lin Lingala lin 63 0.28
tts_test_xho Xhosa xho 242 0.31
tts_test_tsn Tswana tsn 238 0.36
tts_test_afr Afrikaans afr 293 0.34
tts_test_sot Southern Sotho sot 210 0.33
tts_test_Akuapim-twi Akuapim-twi Akuapim-twi 83 0.22

📌 SLID Evaluation

Config Name Language Scope # Samples # Hours
slid_61_test 61 Languages 21,817 34.36

📌 Training data

Config Name Language # Samples (Train / Dev) # Hours (Train / Dev)
asr_train_dev 42 languages 218,515 / 7,500 204.51 / 10.49
slid_train_dev 49 languages 355,337 / 8,529 330.50 / 13.49
tts_train_dev 7 languages 81,729 / 1,347 140.51 / 3.49
TOTAL 655,581 / 17,376 675.52 / 27.47

📖 Citation

If you use the SimbaBench dataset for your scientific publication, or if you find the resources in this repository useful, please cite our paper and the original dataset papers.

📄 SimbaBench Paper

@inproceedings{elmadany-etal-2025-voice,
    title = "Voice of a Continent: Mapping {A}frica{'}s Speech Technology Frontier",
    author = "Elmadany, AbdelRahim A.  and
      Kwon, Sang Yun  and
      Toyin, Hawau Olamide  and
      Alcoba Inciarte, Alcides  and
      Aldarmaki, Hanan  and
      Abdul-Mageed, Muhammad",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.emnlp-main.559/",
    doi = "10.18653/v1/2025.emnlp-main.559",
    pages = "11039--11061",
    ISBN = "979-8-89176-332-6",
}

📄 Original ASR Datasets Citation

Besacier & Gauthier, 2023 — Alffa Public
@misc{besacier-gauthier-2023-alffa,
  author       = {Besacier, Laurent and Gauthier, Elodie},
  title        = {{ALFFA\_PUBLIC}: {A}frican Languages Factored Lattices
                  for Automatic Speech Recognition},
  year         = {2023},
  howpublished = {\url{https://github.com/getalp/ALFFA_PUBLIC}},
}
Sikasote & Anastasopoulos, 2022 — BembaSpeech
@inproceedings{sikasote-anastasopoulos-2022-bembaspeech,
  author    = {Sikasote, Claytone and Anastasopoulos, Antonios},
  title     = {{BembaSpeech}: A Speech Recognition Corpus for the
               Bemba Language},
  booktitle = {Proceedings of the Language Resources and Evaluation
               Conference},
  pages     = {7277--7283},
  year      = {2022},
  address   = {Marseille, France},
  publisher = {European Language Resources Association},
}
Mozilla Foundation, 2023 — Common Voice (CV-19)
@misc{mozilla-2023-commonvoice,
  author       = {{Mozilla Foundation}},
  title        = {Mozilla Common Voice: A Massively Multilingual Open
                  Dataset for Voice Technologies},
  year         = {2023},
  howpublished = {\url{https://commonvoice.mozilla.org}},
}
Asamoah Owusu et al., 2022 — Financial Speech
@misc{asamoahowusu-etal-2022-financialspeech,
  author       = {{Asamoah Owusu}, D. and Korsah, A. and Quartey, B.
                  and {Nwolley Jnr.}, S. and Sampah, D.
                  and Adjepon-Yamoah, D. and {Omane Boateng}, L.},
  title        = {Financial Inclusion Speech Dataset},
  year         = {2022},
  howpublished = {\url{https://github.com/Ashesi-Org/Financial-Inclusion-Speech-Dataset}},
  note         = {Created by Ashesi University and Nokwary Technologies
                  with funding from Lacuna Fund},
}
Gauthier et al., 2024 — Kallaama
@inproceedings{gauthier-etal-2024-kallaama,
  author    = {Gauthier, Elodie and Ndiaye, Aminata and Guissé, Abdoulaye},
  title     = {Kallaama: A Transcribed Speech Dataset about Agriculture
               in the Three Most Widely Spoken Languages in {S}enegal},
  booktitle = {Proceedings of the Fifth Workshop on Resources for
               African Indigenous Languages ({RAIL}) @ {LREC-COLING} 2024},
  year      = {2024},
  address   = {Lannion, France; Dakar and Thiès, Sénégal},
}
Van Heerden et al., 2016 — Lwazi
@inproceedings{vanheerden-etal-2016-lwazi,
  author    = {Van Heerden, Charl and Kleynhans, Neil and Davel, Marelie H.},
  title     = {Improving the {Lwazi} {ASR} Baseline},
  booktitle = {Proceedings of Interspeech 2016},
  year      = {2016},
}
NaijaVoices, 2024 — Naija Voices
@misc{naijavoices-2024,
  author       = {{NaijaVoices}},
  title        = {{NaijaVoices} Dataset: A Multilingual Speech Corpus
                  for {N}igerian Languages},
  year         = {2024},
  howpublished = {\url{https://naijavoices.com/}},
}
Barnard et al., 2014 — NCHLT + AUX1/2
@inproceedings{barnard-etal-2014-nchlt,
  author    = {Barnard, Etienne and Davel, Marelie H. and
               Van Heerden, Charl and De Wet, Febe and Badenhorst, Jaco},
  title     = {The {NCHLT} Speech Corpus of the {S}outh {A}frican Languages},
  booktitle = {Proceedings of the 2014 Spoken Language Technologies for
               Under-resourced Languages ({SLTU}) Workshop},
  pages     = {194--200},
  year      = {2014},
  address   = {St. Petersburg, Russia},
}
Doumbouya et al., 2021 — Nicolingua (0003 & 0004)
@inproceedings{doumbouya-etal-2021-nicolingua,
  author    = {Doumbouya, Moussa and Einstein, Lisa and Piech, Chris},
  title     = {Using Radio Archives for Low-Resource Speech Recognition:
               Towards an Intelligent Virtual Assistant for Illiterate Users},
  booktitle = {Proceedings of the {AAAI} Conference on Artificial Intelligence},
  volume    = {35},
  year      = {2021},
}
Gutkin et al., 2020 — YorubaVoice
@inproceedings{gutkin-etal-2020-yoruba,
  author    = {Gutkin, Alexander and Demirşahin, Işın and
               Kjartansson, Oddur and Rivera, Clara and Túbòsún, Kólá},
  title     = {Developing an Open-Source Corpus of {Y}oruba Speech},
  booktitle = {Proceedings of Interspeech 2020},
  pages     = {404--408},
  year      = {2020},
  address   = {Shanghai, China},
  publisher = {International Speech and Communication Association ({ISCA})},
  doi       = {10.21437/Interspeech.2020-1096},
}
Sikasote et al., 2023 — Zambezi Voice (ASR & Audio Only)
@inproceedings{sikasote-etal-2023-zambezi,
  author    = {Sikasote, Claytone and Siaminwe, Kalinda and Mwape, Stanly
               and Zulu, Bangiwe and Phiri, Mofya and Phiri, Martin
               and Zulu, David and Nyirenda, Mayumbo and Anastasopoulos, Antonios},
  title     = {{Zambezi Voice}: A Multilingual Speech Corpus for {Z}ambian Languages},
  booktitle = {Proc. Interspeech 2023},
  pages     = {3984--3988},
  year      = {2023},
}
Van der Westhuizen & Niesler, 2018 — SO (Code-Switched)
@inproceedings{derwesthuizen-niesler-2018-soap,
  author    = {{Van der Westhuizen}, Ewald and Niesler, Thomas},
  title     = {A First {S}outh {A}frican Corpus of Multilingual Code-switched
               Soap Opera Speech},
  booktitle = {Proceedings of the Eleventh International Conference on
               Language Resources and Evaluation ({LREC} 2018)},
  year      = {2018},
  address   = {Miyazaki, Japan},
  publisher = {European Language Resources Association ({ELRA})},
}
Modipa et al., 2015 — SPCS (Code-Switched)
@inproceedings{modipa-etal-2015-spcs,
  author    = {Modipa, T. I. and Davel, M. H. and De Wet, F.},
  title     = {Implications of {S}epedi/{E}nglish Code Switching for {ASR} Systems},
  booktitle = {Proceedings of the Pattern Recognition Association of
               {S}outh {A}frica ({PRASA})},
  pages     = {112--117},
  year      = {2015},
}

📄 Original SLID Datasets Citation

Doumbouya et al., 2021 — Nicolingua (0003)
@inproceedings{doumbouya-etal-2021-nicolingua,
  author    = {Doumbouya, Moussa and Einstein, Lisa and Piech, Chris},
  title     = {Using Radio Archives for Low-Resource Speech Recognition:
               Towards an Intelligent Virtual Assistant for Illiterate Users},
  booktitle = {Proceedings of the {AAAI} Conference on Artificial Intelligence},
  volume    = {35},
  year      = {2021},
}
The Brick House Cooperative, 2024 — OlongoAfrica
@misc{olongoafrica-2024,
  author       = {{The Brick House Cooperative}},
  title        = {{OlongoAfrica} Multilingual Anthology},
  year         = {2024},
  howpublished = {\url{https://lingua.olongoafrica.com/}},
  note         = {A collection of translated and narrated short stories
                  in various African languages, including Edo, Tamazight,
                  Yoruba, Swahili, Hausa, Tiv, Shona, Ibibio, Igbo,
                  and Nigerian Pidgin},
}
UDHR Audio, 2025 — UDHR
@misc{udhr-audio-2025,
  author       = {{Universal Declaration of Human Rights Audio}},
  title        = {Universal Declaration of Human Rights Audio Project},
  year         = {2025},
  howpublished = {\url{https://udhr.audio/}},
  note         = {Audio recordings of the Universal Declaration of Human
                  Rights in multiple languages},
}
Elmadany et al., 2025 — Voice of Africa (VOA)
@inproceedings{elmadany-etal-2025-simba,
  author    = {Elmadany, AbdelRahim and Kwon, Sang Yun and
               Toyin, Hawau Olamide and Inciarte, Alcides Alcoba and
               Aldarmaki, Hanan and Abdul-Mageed, Muhammad},
  title     = {Voice of a Continent: Mapping {A}frica's Speech
               Technology Frontier},
  booktitle = {Proceedings of the 2025 Conference on Empirical Methods
               in Natural Language Processing},
  pages     = {11028--11050},
  year      = {2025},
  publisher = {Association for Computational Linguistics},
  url       = {https://aclanthology.org/2025.emnlp-main.559},
}
Valk & Alumäe, 2021 — VoxLingua
@inproceedings{valk-alumae-2021-voxlingua,
  author    = {Valk, Jörgen and Alumäe, Tanel},
  title     = {{VoxLingua107}: A Dataset for Spoken Language Recognition},
  booktitle = {Proceedings of the {IEEE} Spoken Language Technology
               Workshop ({SLT})},
  year      = {2021},
}
Sikasote et al., 2023 — Zambezi Voice (Audio Only)
@inproceedings{sikasote-etal-2023-zambezi,
  author    = {Sikasote, Claytone and Siaminwe, Kalinda and Mwape, Stanly
               and Zulu, Bangiwe and Phiri, Mofya and Phiri, Martin
               and Zulu, David and Nyirenda, Mayumbo and Anastasopoulos, Antonios},
  title     = {{Zambezi Voice}: A Multilingual Speech Corpus for {Z}ambian Languages},
  booktitle = {Proc. Interspeech 2023},
  pages     = {3984--3988},
  year      = {2023},
}

📄 Original TTS Datasets Citation

Meyer et al., 2022 — BibleTTS
@inproceedings{meyer-etal-2022-bibletts,
  author    = {Meyer, Josh and Adelani, David and Casanova, Edresson
               and Öktem, Alp and Whitenack, Daniel and Weber, Julian
               and {Kabongo Kabenamualu}, Salomon and Salesky, Elizabeth
               and Orife, Iroro and Leong, Colin and Ogayo, Perez
               and {Chinenye Emezue}, Chris and Mukiibi, Jonathan
               and Osei, Salomey and Agbolo, Apelete and Akinode, Victor
               and Opoku, Bernard and Samuel, Olanrewaju and Alabi, Jesujoba
               and Muhammad, Shamsuddeen Hassan},
  title     = {{BibleTTS}: A Large, High-Fidelity, Multilingual, and
               Uniquely {A}frican Speech Corpus},
  booktitle = {Interspeech 2022},
  pages     = {2383--2387},
  year      = {2022},
  address   = {Incheon, Korea},
  publisher = {ISCA},
  doi       = {10.21437/Interspeech.2022-10850},
}
van Niekerk et al., 2017 — High-Quality TTS (SA)
@inproceedings{vanniekerk-etal-2017-hqtts,
  author    = {van Niekerk, Daniel and van Heerden, Charl and Davel, Marelie
               and Kleynhans, Neil and Kjartansson, Oddur and Jansche, Martin
               and Ha, Linne},
  title     = {Rapid Development of {TTS} Corpora for Four {S}outh {A}frican Languages},
  booktitle = {Interspeech 2017},
  pages     = {2178--2182},
  year      = {2017},
  address   = {Stockholm, Sweden},
  publisher = {ISCA},
  doi       = {10.21437/Interspeech.2017-1139},
}
Digital Umuganda, 2023 — Kinyarwanda TTS
@misc{digitalumuganda-2023-kinyarwanda,
  author       = {{Digital Umuganda}},
  title        = {{AfriSpeech} {K}inyarwanda Male and Female {TTS} Datasets},
  year         = {2023},
  howpublished = {\url{https://huggingface.co/datasets/DigitalUmuganda/afrispeak_kinyarwanda_male_tts_dataset}},
}
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