annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
multilinguality:
- multilingual
language:
- sn
- ln
license: cc-by-4.0
Dataset Card for the image text and voice dataset
Dataset Description
Dataset Summary
This dataset consists of a unique JPEG image, a corresponding audio WAV file describing the image, and when available, the transcription of the audio file. The Shona dataset has a total of 574.16 hours of audio; out of which, 100 hours have transcriptions and the remaining 474.16 hours do not have a corresponding transcribed text. For Lingala, the dataset is 517.13 hours long, with 100.98 hours transcribed and 416.15 hours with no transcriptions.
Languages
Shona, Lingala
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.
To download the config, specify the language code (i.e., "sn" for shona, and "ln" for lingala):
from datasets import load_dataset
data = load_dataset("DigitalUmuganda/AfriVoice", "sn")
Dataset Structure
Data Instances
{'creator': 'digital_umuganda',
'project_name': 'shona_data_collection',
'speaker_id': '2Eud8lyLlsMcciYhmlkwVRtBwi82',
'audio_path': '/root/.cache/huggingface/datasets/downloads/extracted/9347eb035e3ae38aaf793efa152ba1c93a4336471afce2bbd00ac8c0f67e9066/small_data/audio/I7L1YJVKIRL4.wav',
'image_path': '/root/.cache/huggingface/datasets/downloads/extracted/9347eb035e3ae38aaf793efa152ba1c93a4336471afce2bbd00ac8c0f67e9066/small_data/image/I7L1YJVKIRL4.jpeg',
'transcription': 'Varume vaviri vari kukandirana bhora. Varume ava vakapfeka zvipika zvine ruvara rutema neruchena. Zvikabudura zvine ruvara rutema. Bhora ravanokandirana rine ruvara rweyero neruchena nerwebhuruu. Vari kutambira munhandare ine ivhu. Kumashure kwavo kwakagara vanhu.',
'locale': 'sn_ZW',
'gender': 'Female',
'age': ' ',
'year': '2023'}
Data Fields
creator (string): An id for which client (voice) made the recording
image_path (string): The path to the audio file
path_audio (string): The path to the image file
transcription (string): The sentence the user was prompted to speak
age (string): The age of the speaker
gender (string): The gender of the speaker
project_name (string): Name of the project
locale (string): The locale of the speaker
year (string): Year of recording
Data Splits
Currently to data not yet split ie to access you must precise the train option, however the dataset will be split into train, dev, and test at some point in the future.