Access over 1 million hours of transcribed recordings from across Africa
Enhance Your AI Models with Genuine Human Voices and Diverse Accents for Unmatched Linguistic and Cultural Precision
Available Recordings
Country | Language | Total hours |
Algeria | Arabic | 1340.5 |
English | 50 | |
Angola | English | 50 |
Fiote | 50 | |
Portuguese | 27330 | |
Quicongo | 50 | |
Umbundu | 50 | |
Benin | Fon | 50 |
French | 814 | |
Botswana | English | 581.5 |
Setswana | 582 | |
Burkina-Faso | Dioula | 50 |
Dyula | 4125 | |
English | 50 | |
French | 13005 | |
Moré | 19777.5 | |
Burundi | English | 50 |
French | 115 | |
Kirundi | 141.5 | |
Cameroon | English | 8300 |
Foulbe | 50 | |
French | 27988 | |
Fula | 94.5 | |
Central African Republic | French | 7200.5 |
Sango | 31279.5 | |
Chad | Arabic | 406.5 |
Chadian Arabic | 21414.5 | |
French | 12908 | |
Kanembou | 50 | |
Sara | 3918.5 | |
Comoros | Comorian | 1013.5 |
French | 487 | |
Shikomoro | 323.5 | |
Congo | French | 8436.5 |
Kituba | 1098 | |
Lingala | 764 | |
Democratic Republic of the Congo | English | 50 |
French | 36639 | |
Kikongo | 50 | |
Kiswahili | 3937 | |
Lingala | 19042.5 | |
Tshiluba | 50 | |
Djibouti | Afar | 146.5 |
Arabic | 287.5 | |
French | 50 | |
Somali | 173 | |
Egypt | Arabic | 1515.5 |
English | 50 | |
Eritrea | English | 50 |
Tigrinya | 690.5 | |
Ethiopia | Afar | 483 |
Amharic | 36323.5 | |
Anuak | 50 | |
Arabic | 50 | |
English | 105.5 | |
Nuer | 50 | |
Oromo | 4792 | |
Somali | 6188.5 | |
Tigrinya | 1600.5 | |
Gambia | English | 536.5 |
Mandinka | 131 | |
Wolof | 98.5 | |
Ghana | Akan | 90.5 |
Dagbani | 50 | |
English | 7151.5 | |
Ewe | 78 | |
Ga | 50 | |
Twi | 1074 | |
Guinea | French | 9795 |
Fula | 5270.5 | |
Guerze | 50 | |
Kissi | 412 | |
Kpelle | 610 | |
Malinke | 5441 | |
Susu | 3414.5 | |
Toma | 83 | |
Ivory Coast (Cote D’Ivoire) | English | 50 |
French | 3268.5 | |
Malinke | 50 | |
Kenya | English | 63051.5 |
French | 50 | |
Kiswahili | 83659.5 | |
Somali | 652.5 | |
Lesotho | English | 426.5 |
Sotho | 337 | |
Madagascar | Atanosy | 50 |
Mahafaly | 50 | |
Malagasy | 1040 | |
Tandory | 50 | |
Malawi | Chichewa | 54256.5 |
English | 456.5 | |
Tumbuka | 50 | |
Mali | Bambara | 18681.5 |
Dogon | 50 | |
French | 3152 | |
Tamachek | 50 | |
Mauritania | Arabic | 423 |
French | 428 | |
Hassaniya | 987 | |
Soninke | 50 | |
Wolof | 54.5 | |
Morocco | Arabic | 258.5 |
English | 50 | |
Moroccan Arabic | 518.5 | |
Mozambique | Changana | 83 |
Emakhuwa | 64 | |
English | 50 | |
Maconde | 50 | |
Macua | 50 | |
Portuguese | 8698.5 | |
Xichangana | 113.5 | |
Namibia | Afrikaans | 272.5 |
English | 8782.5 | |
Oshikwanyama | 8049.5 | |
Oshiwambo | 64.5 | |
Oshondonga | 1598.5 | |
Rukwangali | 50 | |
Setswana | 50 | |
Silozi | 62 | |
Niger | Djerma | 6393.5 |
French | 3065.5 | |
Hausa | 29498.5 | |
Kanuri | 50 | |
Zarma | 1067 | |
Nigeria | English | 133464.5 |
Hausa | 36294 | |
Igbo | 233 | |
Kanuri | 2979.5 | |
Pidgin | 1353.5 | |
Yoruba | 1223.5 | |
Rwanda | English | 64 |
Kinyarwanda | 3524.5 | |
Senegal | English | 50 |
French | 2510 | |
Wolof | 666 | |
Sierra Leone | English | 2118 |
Krio | 41534.5 | |
Limba | 50 | |
Mende | 183.5 | |
Temne | 101 | |
Somalia | Arabic | 52 |
English | 758.5 | |
Somali | 37348.5 | |
South Africa | Afrikaans | 61.5 |
English | 10577.5 | |
Sepedi | 182.5 | |
Setswana | 50 | |
Xhosa | 688 | |
Zulu | 1591.5 | |
South Sudan | Eastern Dinka | 88 |
English | 547.5 | |
Juba Arabic | 270.5 | |
Rek Dinka | 64 | |
Sudan | Arabic | 693.5 |
English | 50 | |
Swaziland | English | 1009.5 |
Siswati | 2324.5 | |
Tanzania | English | 145.5 |
Kiswahili | 55143.5 | |
Uganda | Acholi | 50 |
Aringa | 50 | |
Ateso | 50 | |
English | 25066 | |
Kiswahili | 1631 | |
Langi | 50 | |
Luganda | 8825.5 | |
Lugbara | 58.5 | |
Luo | 50 | |
Lutooro | 50 | |
Maadi | 50 | |
Ngakarimojong | 1112 | |
Runyankole | 50 | |
Runyankore | 72 | |
Zambia | Bemba | 12133 |
English | 10926.5 | |
Lozi | 103.5 | |
Nyanja | 13130.5 | |
Tonga | 733 | |
Zimbabwe | English | 2719.5 |
Ndebele | 3294.5 | |
Shona | 36407.5 | |
Grand Total | 1,096,422 |
The Value
Human-Written Transcripts
Our recordings come with meticulously human-written transcripts, ensuring the highest level of accuracy and authenticity. This attention to detail allows your AI models to learn from precise and contextually relevant data, improving their natural language processing capabilities.
Representative
With over 1 million hours of recordings, our dataset captures a wide range of dialects, accents, and languages from across Africa. This representative data enables your AI to understand and interact with diverse linguistic and cultural nuances, making your applications more inclusive and effective.
High-Quality Voice and Video
Our recordings are of exceptional quality, featuring clear audio and high-definition video. This ensures that your AI models are trained on the best possible data, leading to more accurate speech recognition, sentiment analysis, and other advanced AI functionalities.
Privacy and Compliance
We prioritize user privacy and adhere to stringent data protection standards. Our data collection methods are ethically sound and compliant with international regulations, ensuring that your use of our datasets respects user rights and maintains trust.
Get the data
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