Sunbird African Language Technology (SALT) dataset

SALT is a multi-way parallel text and speech corpus of Engish and six languages widely spoken in Uganda and East Africa: Luganda, Lugbara, Acholi, Runyankole, Ateso and Swahili. The core of the dataset is a set of 25,000 sentences covering a range of topics of local relevance, such as agriculture, health and society. Each sentence is translated into all languages, to support machine translation, and speech recordings are made for approximately 5,000 of the sentences both by a variety of speakers in natural settings (suitable for ASR) and by professionals in a studio setting (suitable for text-to-speech).

Subsets

Subset name	Contents
text-all	Text translations of each sentence.
multispeaker-{lang}	Speech recordings of each sentence, by a variety of speakers in natural settings.
studio-{lang}	Speech recordings in a studio setting, suitable for text-to-speech.

The sentence IDs map across subsets, so that for example the text of a sentence in Acholi can be mapped to the studio recording of that concept being expressed in Swahili. The subsets can therefore be combined to support the training and evaluation of several further tasks, such as speech-to-text translation and speech-to-speech translation.

Language support

ISO 639-3	Language	Translated text	Multispeaker speech	Studio speech
eng	English (Ugandan accent)	Yes	Yes	Yes
lug	Luganda	Yes	Yes	Yes
ach	Acholi	Yes	Yes	Yes
lgg	Lugbara	Yes	Yes	Yes
teo	Ateso	Yes	Yes	Yes
nyn	Runyankole	Yes	Yes	Yes
swa	Swahili	Yes	No	Yes
ibo	Igbo	Yes	No	No

Helper utilities

Code for convenient experimentation with multilingual models can be found at https://github.com/SunbirdAI/salt. See example notebooks here.

Collaborators

This dataset was collected in practical collaboration between Sunbird AI and the Makerere University AI Lab (Ugandan languages) and KenCorpus, Maseno University (Swahili).

Reference

Machine Translation For African Languages: Community Creation Of Datasets And Models In Uganda. Benjamin Akera, Jonathan Mukiibi, Lydia Sanyu Naggayi, Claire Babirye, Isaac Owomugisha, Solomon Nsumba, Joyce Nakatumba-Nabende, Engineer Bainomugisha, Ernest Mwebaze, John Quinn. 3rd Workshop on African Natural Language Processing, 2022.