Domain	Total Hours	Transcribed Hours	Number of Clips	Dataset Size (GB)
Agriculture	713.3	692.11	124,648	24.208
Education	408.43	392.33	70,745	14.439
Finance	611.66	601.15	105,763	24.127
Government	578.14	566.15	101,021	23.921
Health	668.29	608.33	118,827	22.438
Total	2979.81	2860.07	521,004	109.133

How to use

The datasets library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the load_dataset function.

For full dataset

from datasets import load_dataset
data = load_dataset("DigitalUmuganda/Afrivoice_Swahili")

For categorical dataset

from datasets import load_dataset
data = load_dataset("DigitalUmuganda/Afrivoice_Swahili", name="health")

The categories options are:

agriculture
education
financial
government
health

Dataset Structure

Data Instance

{
    "voice_creator_id":"Pz7I1psEYicM9DqX6vGIZPTCb8s1",
    "transcription_creator_id":"kUOiFZjsGiT2DyXUfILN9rujKQJ2",
    "image_filepath":"download (23).jpg",
    "image_category":"health",
    "image_sub_category":"conferences",
    "category":"health",
    "audio_filepath":"1755180107-Pz7I1psEYicM9DqX6vGIZPTCb8s1.webm",
    "transcription":"Kuna mkusanyiko wa watu wengi katika ukumbi wakisoma vitabu vya dini. Inaonekana ni mkutano wa bibilia wa kanisa la Kenya la shirika la makanisa ya Kenya. Hii inahusiana na makongamano au mikutano ya kidini.",
    "normalized_transcription":"kuna mkusanyiko wa watu wengi katika ukumbi wakisoma vitabu vya dini inaonekana ni mkutano wa bibilia wa kanisa la kenya la shirika la makanisa ya kenya hii inahusiana na makongamano au mikutano ya kidini",
    "age_group":"25-35",
    "gender":"Male",
    "project_name":"Digital Umuganda",
    "locale":"sw_KE",
    "year":2025,
    "duration":17.58,
    "location":"Nairobi",
    "uid":"Pz7I1psEYicM9DqX6vGIZPTCb8s1",
    "key":"4KKR4f9VC7za27mJAjso",
    "dir_path":"health_swahili_test",
    "chunk_id":0
}

Data Fields

voice_creator_id (string): An id for which client (voice) made the recording

transcription_creator_id (string): An id for which client (text) made the transcription

transcription (string): Original audio transcription with punctuation and capitalization

normalized_transcription (string): Original audio transcription without punctuation and capitalization

image_filepath (string): file path of the image file inside the dataset

audio_filepath (string): file path of the audio file inside the dataset

dir_path (string): main directory path of the record

chunk_id (string): chunk identification number where the record belong

age_group (string): age range of the audio recorder

gender (string): The gender of the speaker

location (string): geographical location of the audio recorder

duration (int): length in seconds of the audio file

image_category (string): domain of the image (eg: health, agriculture, finance), used as prompt during audio creation.

image_sub_category (string): Sub-domain label of the image (e.g., within agriculture: “seed farming” or “forestry”), used to guide audio creation.

category (string): category of the record

project (string): project name

locale (string): The locale of the speaker

year (int): Year of recording

project_name (string): project name

location (string): location of the project

key (string): key identifier of the data point

Licensing Information

All datasets are licensed under the Creative Commons license (CC-BY-4).

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