Datasets:
metadata
dataset_info:
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configs:
- config_name: multispeaker-ach
data_files:
- split: train
path: multispeaker-ach/train-*
- split: dev
path: multispeaker-ach/dev-*
- split: test
path: multispeaker-ach/test-*
- config_name: multispeaker-eng
data_files:
- split: train
path: multispeaker-eng/train-*
- split: dev
path: multispeaker-eng/dev-*
- split: test
path: multispeaker-eng/test-*
- config_name: multispeaker-lgg
data_files:
- split: train
path: multispeaker-lgg/train-*
- split: dev
path: multispeaker-lgg/dev-*
- split: test
path: multispeaker-lgg/test-*
- config_name: multispeaker-lug
data_files:
- split: train
path: multispeaker-lug/train-*
- split: dev
path: multispeaker-lug/dev-*
- split: test
path: multispeaker-lug/test-*
- config_name: multispeaker-nyn
data_files:
- split: train
path: multispeaker-nyn/train-*
- split: dev
path: multispeaker-nyn/dev-*
- split: test
path: multispeaker-nyn/test-*
- config_name: multispeaker-teo
data_files:
- split: train
path: multispeaker-teo/train-*
- split: dev
path: multispeaker-teo/dev-*
- split: test
path: multispeaker-teo/test-*
- config_name: studio-ach
data_files:
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path: studio-ach/train-*
- split: dev
path: studio-ach/dev-*
- split: test
path: studio-ach/test-*
- config_name: studio-eng
data_files:
- split: train
path: studio-eng/train-*
- split: dev
path: studio-eng/dev-*
- split: test
path: studio-eng/test-*
- config_name: studio-lgg
data_files:
- split: train
path: studio-lgg/train-*
- split: dev
path: studio-lgg/dev-*
- split: test
path: studio-lgg/test-*
- config_name: studio-lug
data_files:
- split: train
path: studio-lug/train-*
- split: dev
path: studio-lug/dev-*
- split: test
path: studio-lug/test-*
- config_name: studio-nyn
data_files:
- split: train
path: studio-nyn/train-*
- split: dev
path: studio-nyn/dev-*
- split: test
path: studio-nyn/test-*
- config_name: studio-swa
data_files:
- split: train
path: studio-swa/train-*
- split: dev
path: studio-swa/dev-*
- split: test
path: studio-swa/test-*
- config_name: studio-teo
data_files:
- split: train
path: studio-teo/train-*
- split: dev
path: studio-teo/dev-*
- split: test
path: studio-teo/test-*
- config_name: text-all
data_files:
- split: train
path: text-all/train-*
- split: dev
path: text-all/dev-*
- split: test
path: text-all/test-*
- config_name: text-hard
data_files:
- split: train
path: text-hard/train-*
license: cc-by-sa-4.0
task_categories:
- automatic-speech-recognition
- text-to-speech
- translation
language:
- ach
- eng
- lgg
- lg
- nyn
- teo
- ttj
- sw
- xog
pretty_name: Sunbird African Language Technology (SALT) dataset
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. |
| text-hard | 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 |
| ttj | Rutooro | Yes | No | No |
| xog | Lusoga | 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.