| | --- |
| | 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: asr |
| | data_files: |
| | - split: train |
| | path: "data/ASR/**/*-train-*" |
| | - split: validation |
| | path: "data/ASR/**/*-validation-*" |
| | - split: test |
| | path: "data/ASR/**/*-test-*" |
| | - split: unlabeled |
| | path: "data/ASR/**/*-unlabeled-*" |
| | - config_name: tts |
| | data_files: |
| | - split: train |
| | path: "data/TTS/**/*-train-*" |
| | - split: validation |
| | path: "data/TTS/**/*-validation-*" |
| | - split: test |
| | path: "data/TTS/**/*-test-*" |
| | dataset_info: |
| | - config_name: 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: tts |
| | features: |
| | - name: id |
| | dtype: string |
| | - name: speaker_id |
| | dtype: string |
| | - name: transcription |
| | 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-NC-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-NC-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: |
| |
|
| | ```bash |
| | pip install datasets[audio] |
| | ``` |
| |
|
| | **Loading ASR Data** |
| |
|
| | To load ASR data, point to the `data/ASR` directory. |
| |
|
| | ```python |
| | from datasets import load_dataset, Audio |
| | |
| | # Load Shona (sna) ASR dataset |
| | asr_data = load_dataset("google/WaxalNLP", "sna", data_dir="data/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, point to the `data/TTS` directory. |
| |
|
| | ```python |
| | from datasets import load_dataset |
| | |
| | # Load Swahili (swa) TTS dataset |
| | tts_data = load_dataset("google/WaxalNLP", "swa", data_dir="data/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 |
| | }, |
| | 'transcription': '...', |
| | 'locale': 'swa', |
| | 'gender': 'Female', |
| | } |
| | ``` |
| | |
| | * **id**: Unique identifier. |
| | * **speaker_id**: Unique identifier for the speaker. |
| | * **audio**: Audio data. |
| | * **transcription**: Transcription. |
| | * **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 |
| |
|
