Datasets:
Dataset Card for the image text and voice dataset
Dataset Description
This is an image prompt ASR dataset for Swahili. The dataset was collected on 5 domains: Agriculture, Education, Finance, Government and Health.
| 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":"3bqVVjMdPtUg3YDJE2T0b8jUuTq1",
"transcription_creator_id":"GZbQSWNUOoZDNgTSKlz7ZZgXAHC2",
"image_filepath":"32749ce.jpg",
"image_category":"agriculture",
"image_sub_category":"food banks",
"category":"agriculture",
"audio_filepath":"xadnlONijhyVvN2USCkF.webm",
"transcription":"Kuna wamama watatu ambao wanaonekana karibu na magunia ambayo ni ya rangi nyeupe, na pia kuna [cs]katoni[cs], karibu nao kuna mlima ambao unaonekana pamoja na mahindi, na juu pia kuna mawingu ya rangi nyeupe, na ya rangi ya samawati.",
"normalized_transcription":"kuna wamama watatu ambao wanaonekana karibu na magunia ambayo ni ya rangi nyeupe na pia kuna cskatonics karibu nao kuna mlima ambao unaonekana pamoja na mahindi na juu pia kuna mawingu ya rangi nyeupe na ya rangi ya samawati",
"age_group":"25-35",
"gender":"Male",
"project_name":"Digital Umuganda",
"locale":"sw_KE",
"year":2025,
"duration":18.3,
"location":null,
"uid":"3bqVVjMdPtUg3YDJE2T0b8jUuTq1",
"key":"xadnlONijhyVvN2USCkF",
"dir_path":"agriculture_swahili_dev",
"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).
- Downloads last month
- 131