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WaxalNLP

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Automatic Speech Recognition
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 ---
license:
- cc-by-sa-4.0
- cc-by-4.0
annotation_creators:
- human-annotated
- crowdsourced
language_creators:
- creator_1
tags:
- audio
- automatic-speech-recognition
- text-to-speech
language:
- ach
- aka
- dag
- dga
- ewe
- fat
- ful
- hau
- ibo
- kpo
- lin
- lug
- mas
- mlg
- nyn
- sna
- sog
- swa
- twi
- yor
multilinguality:
- multilingual
pretty_name: Waxal NLP Datasets
task_categories:
- automatic-speech-recognition
- text-to-speech
source_datasets:
- UGSpeechData
- DigitalUmuganda/AfriVoice
- original
configs:
- config_name: ach_asr
data_files:
- split: train
path: "data/ASR/ach/ach-train-*"
- split: validation
path: "data/ASR/ach/ach-validation-*"
- split: test
path: "data/ASR/ach/ach-test-*"
- split: unlabeled
path: "data/ASR/ach/ach-unlabeled-*"
- config_name: ach_tts
data_files:
- split: train
path: "data/TTS/ach/ach-train-*"
- split: validation
path: "data/TTS/ach/ach-validation-*"
- split: test
path: "data/TTS/ach/ach-test-*"
- config_name: aka_asr
data_files:
- split: train
path: "data/ASR/aka/aka-train-*"
- split: validation
path: "data/ASR/aka/aka-validation-*"
- split: test
path: "data/ASR/aka/aka-test-*"
- split: unlabeled
path: "data/ASR/aka/aka-unlabeled-*"
- config_name: dag_asr
data_files:
- split: train
path: "data/ASR/dag/dag-train-*"
- split: validation
path: "data/ASR/dag/dag-validation-*"
- split: test
path: "data/ASR/dag/dag-test-*"
- split: unlabeled
path: "data/ASR/dag/dag-unlabeled-*"
- config_name: dga_asr
data_files:
- split: train
path: "data/ASR/dga/dga-train-*"
- split: validation
path: "data/ASR/dga/dga-validation-*"
- split: test
path: "data/ASR/dga/dga-test-*"
- split: unlabeled
path: "data/ASR/dga/dga-unlabeled-*"
- config_name: ewe_asr
data_files:
- split: train
path: "data/ASR/ewe/ewe-train-*"
- split: validation
path: "data/ASR/ewe/ewe-validation-*"
- split: test
path: "data/ASR/ewe/ewe-test-*"
- split: unlabeled
path: "data/ASR/ewe/ewe-unlabeled-*"
- config_name: fat_tts
data_files:
- split: train
path: "data/TTS/fat/fat-train-*"
- split: validation
path: "data/TTS/fat/fat-validation-*"
- split: test
path: "data/TTS/fat/fat-test-*"
- config_name: ful_asr
data_files:
- split: train
path: "data/ASR/ful/ful-train-*"
- split: validation
path: "data/ASR/ful/ful-validation-*"
- split: test
path: "data/ASR/ful/ful-test-*"
- split: unlabeled
path: "data/ASR/ful/ful-unlabeled-*"
- config_name: ful_tts
data_files:
- split: train
path: "data/TTS/ful/ful-train-*"
- split: validation
path: "data/TTS/ful/ful-validation-*"
- split: test
path: "data/TTS/ful/ful-test-*"
- config_name: hau_tts
data_files:
- split: train
path: "data/TTS/hau/hau-train-*"
- split: validation
path: "data/TTS/hau/hau-validation-*"
- split: test
path: "data/TTS/hau/hau-test-*"
- config_name: ibo_tts
data_files:
- split: train
path: "data/TTS/ibo/ibo-train-*"
- split: validation
path: "data/TTS/ibo/ibo-validation-*"
- split: test
path: "data/TTS/ibo/ibo-test-*"
- config_name: kpo_asr
data_files:
- split: train
path: "data/ASR/kpo/kpo-train-*"
- split: validation
path: "data/ASR/kpo/kpo-validation-*"
- split: test
path: "data/ASR/kpo/kpo-test-*"
- split: unlabeled
path: "data/ASR/kpo/kpo-unlabeled-*"
- config_name: lin_asr
data_files:
- split: train
path: "data/ASR/lin/lin-train-*"
- split: validation
path: "data/ASR/lin/lin-validation-*"
- split: test
path: "data/ASR/lin/lin-test-*"
- split: unlabeled
path: "data/ASR/lin/lin-unlabeled-*"
- config_name: lug_asr
data_files:
- split: train
path: "data/ASR/lug/lug-train-*"
- split: validation
path: "data/ASR/lug/lug-validation-*"
- split: test
path: "data/ASR/lug/lug-test-*"
- split: unlabeled
path: "data/ASR/lug/lug-unlabeled-*"
- config_name: lug_tts
data_files:
- split: train
path: "data/TTS/lug/lug-train-*"
- split: validation
path: "data/TTS/lug/lug-validation-*"
- split: test
path: "data/TTS/lug/lug-test-*"
- config_name: mas_asr
data_files:
- split: train
path: "data/ASR/mas/mas-train-*"
- split: validation
path: "data/ASR/mas/mas-validation-*"
- split: test
path: "data/ASR/mas/mas-test-*"
- split: unlabeled
path: "data/ASR/mas/mas-unlabeled-*"
- config_name: mlg_asr
data_files:
- split: train
path: "data/ASR/mlg/mlg-train-*"
- split: validation
path: "data/ASR/mlg/mlg-validation-*"
- split: test
path: "data/ASR/mlg/mlg-test-*"
- split: unlabeled
path: "data/ASR/mlg/mlg-unlabeled-*"
- config_name: nyn_asr
data_files:
- split: train
path: "data/ASR/nyn/nyn-train-*"
- split: validation
path: "data/ASR/nyn/nyn-validation-*"
- split: test
path: "data/ASR/nyn/nyn-test-*"
- split: unlabeled
path: "data/ASR/nyn/nyn-unlabeled-*"
- config_name: nyn_tts
data_files:
- split: train
path: "data/TTS/nyn/nyn-train-*"
- split: validation
path: "data/TTS/nyn/nyn-validation-*"
- split: test
path: "data/TTS/nyn/nyn-test-*"
- config_name: sna_asr
data_files:
- split: train
path: "data/ASR/sna/sna-train-*"
- split: validation
path: "data/ASR/sna/sna-validation-*"
- split: test
path: "data/ASR/sna/sna-test-*"
- split: unlabeled
path: "data/ASR/sna/sna-unlabeled-*"
- config_name: sog_asr
data_files:
- split: train
path: "data/ASR/sog/sog-train-*"
- split: validation
path: "data/ASR/sog/sog-validation-*"
- split: test
path: "data/ASR/sog/sog-test-*"
- split: unlabeled
path: "data/ASR/sog/sog-unlabeled-*"
- config_name: swa_tts
data_files:
- split: train
path: "data/TTS/swa/swa-train-*"
- split: validation
path: "data/TTS/swa/swa-validation-*"
- split: test
path: "data/TTS/swa/swa-test-*"
- config_name: twi_tts
data_files:
- split: train
path: "data/TTS/twi/twi-train-*"
- split: validation
path: "data/TTS/twi/twi-validation-*"
- split: test
path: "data/TTS/twi/twi-test-*"
- config_name: yor_tts
data_files:
- split: train
path: "data/TTS/yor/yor-train-*"
- split: validation
path: "data/TTS/yor/yor-validation-*"
- split: test
path: "data/TTS/yor/yor-test-*"
dataset_info:
- config_name: ach_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: ach_tts
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: text
dtype: string
- name: locale
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: aka_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: dag_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: dga_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: ewe_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: fat_tts
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: text
dtype: string
- name: locale
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: ful_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: ful_tts
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: text
dtype: string
- name: locale
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: hau_tts
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: text
dtype: string
- name: locale
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: ibo_tts
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: text
dtype: string
- name: locale
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: kpo_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: lin_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: lug_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: lug_tts
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: text
dtype: string
- name: locale
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: mas_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: mlg_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: nyn_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: nyn_tts
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: text
dtype: string
- name: locale
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: sna_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: sog_asr
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: transcription
dtype: string
- name: language
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: swa_tts
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: text
dtype: string
- name: locale
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: twi_tts
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: text
dtype: string
- name: locale
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
- config_name: yor_tts
features:
- name: id
dtype: string
- name: speaker_id
dtype: string
- name: text
dtype: string
- name: locale
dtype: string
- name: gender
dtype: string
- name: audio
dtype: audio
---
# Waxal Datasets
## Table of Contents
- [Dataset Description](#dataset-description)
- [ASR Dataset](#asr-dataset)
- [TTS Dataset](#tts-dataset)
- [How to Use](#how-to-use)
- [Dataset Structure](#dataset-structure)
- [ASR Data Fields](#asr-data-fields)
- [TTS Data Fields](#tts-data-fields)
- [Data Splits](#data-splits)
- [Dataset Curation](#dataset-curation)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Additional Information](#additional-information)
## Dataset Description
The Waxal project provides datasets for both Automated Speech Recognition (ASR)
and Text-to-Speech (TTS) for African languages. The goal of this dataset's
creation and release is to facilitate research that improves the accuracy and
fluency of speech and language technology for these underserved languages, and
to serve as a repository for digital preservation.
The Waxal datasets are collections acquired through partnerships with Makerere
University, The University of Ghana, Digital Umuganda, and Media Trust.
Acquisition was funded by Google and the Gates Foundation under an agreement to
make the dataset openly accessible.
### ASR Dataset
The Waxal ASR dataset is a collection of data in 14 African languages. It
consists of approximately 1,250 hours of transcribed natural speech from a wide
variety of voices. The 14 languages in this dataset represent over 100 million
speakers across 40 Sub-Saharan African countries.
Provider | Languages | License
:------------------ | :--------------------------------------- | :------------:
Makerere University | Acholi, Luganda, Masaaba, Nyankole, Soga | `CC-BY-4.0`
University of Ghana | Akan, Ewe, Dagbani, Dagaare, Ikposo | `CC-BY-4.0`
Digital Umuganda | Fula, Lingala, Shona, Malagasy | `CC-BY-4.0`
### TTS Dataset
The Waxal TTS dataset is a collection of text-to-speech data in 10 African
languages. It consists of approximately 240 hours of scripted natural speech
from a wide variety of voices.
Provider | Languages | License
:------------------ | :----------------------------------- | :------------:
Makerere University | Acholi, Luganda, Kiswahili, Nyankole | `CC-BY-4.0`
University of Ghana | Akan (Fante, Twi) | `CC-BY-4.0`
Media Trust | Fula, Igbo, Hausa, Yoruba | `CC-BY-4.0`
### How to Use
The `datasets` library allows you to load and pre-process your dataset in pure
Python, at scale.
First, ensure you have the necessary dependencies installed to handle audio
data. You will need `ffmpeg` installed on your system.
**Google Colab / Ubuntu**
```bash
sudo apt-get install ffmpeg
pip install datasets[audio]
```
**macOS**
```bash
brew install ffmpeg
pip install datasets[audio]
```
**Windows**
Download and install from [ffmpeg.org](https://ffmpeg.org/download.html) and ensure it's in your PATH.
```bash
pip install datasets[audio]
```
If you encounter `RuntimeError: Could not load libtorchcodec`, please ensure `ffmpeg` is correctly installed or check for compatibility between your `torch`, `torchaudio`, and `torchcodec` versions.
**Loading ASR Data**
To load ASR data for a specific language, specify the configuration name, e.g.
`sna_asr` for Shona ASR data.
```python
from datasets import load_dataset, Audio
# Load Shona (sna) ASR dataset
asr_data = load_dataset("google/WaxalNLP", "sna_asr")
# Access splits
train = asr_data['train']
val = asr_data['validation']
test = asr_data['test']
# Example: Accessing audio bytes and other fields
example = train[0]
print(f"Transcription: {example['transcription']}")
print(f"Sampling Rate: {example['audio']['sampling_rate']}")
# 'array' contains the decoded audio bytes as a numpy array
print(f"Audio Array Shape: {example['audio']['array'].shape}")
```
**Loading TTS Data**
To load TTS data for a specific language, specify the configuration name, e.g.
`swa_tts` for Swahili TTS data.
```python
from datasets import load_dataset
# Load Swahili (swa) TTS dataset
tts_data = load_dataset("google/WaxalNLP", "swa_tts")
# Access splits
train = tts_data['train']
```
## Dataset Structure
### ASR Data Fields
```python
{
'id': 'sna_0',
'speaker_id': '...',
'audio': {
'array': [...],
'sample_rate': 16_000
},
'transcription': '...',
'language': 'sna',
'gender': 'Female',
}
```
* **id**: Unique identifier.
* **speaker_id**: Unique identifier for the speaker.
* **audio**: Audio data.
* **transcription**: Transcription of the audio.
* **language**: ISO 639-2 language code.
* **gender**: Speaker gender ('Male', 'Female', or empty).
### TTS Data Fields
```python
{
'id': 'swa_0',
'speaker_id': '...',
'audio': {
'array': [...],
'sample_rate': 16_000
},
'text': '...',
'locale': 'swa',
'gender': 'Female',
}
```
* **id**: Unique identifier.
* **speaker_id**: Unique identifier for the speaker.
* **audio**: Audio data.
* **text**: Text script.
* **locale**: ISO 639-2 language code.
* **gender**: Speaker gender.
### Data Splits
For the **ASR Dataset**, the data with transcriptions is split as follows: *
**train**: 80% of labeled data. * **validation**: 10% of labeled data. *
**test**: 10% of labeled data.
The **unlabeled** split contains all samples that do not have a corresponding
transcription.
The **TTS Dataset** follows a similar structure, with data split into `train`,
`validation`, and `test` sets.
## Dataset Curation
The data was gathered by multiple partners:
Provider | Dataset | License
:------------------ | :------------------------------------------------------- | :------
University of Ghana | [UGSpeechData](https://doi.org/10.57760/sciencedb.22298) | `CC BY 4.0`
Digital Umuganda | [AfriVoice](DigitalUmuganda/AfriVoice) | `CC-BY 4.0`
Makerere University | [Yogera Dataset](https://doi.org/10.7910/DVN/BEROE0) | `CC-BY 4.0`
Media Trust | | `CC-BY 4.0`
## Considerations for Using the Data
Please check the license for the specific languages you are using, as they may
differ between providers.
**Affiliation:** Google Research
## Version and Maintenance
- **Current Version:** 1.0.0
- **Last Updated:** 01/2026