Waxal Datasets Table of Contents Dataset Description ASR Dataset TTS Dataset How to Use Dataset Structure ASR Data Fields TTS Data Fields Data Splits Dataset Curation Considerations for Using the Data 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 19 African languages. It consists of approximately 1,250 hours of transcribed natural speech from a wide variety of voices. The 19 languages in this dataset represent over 100 million speakers across 40 Sub Saharan African countries. Provider Languages License : :…
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