  This work introduces Zambezi Voice, an open-source multilingual speech
resource for Zambian languages. It contains two collections of datasets:
unlabelled audio recordings of radio news and talk shows programs (160 hours)
and labelled data (over 80 hours) consisting of read speech recorded from text
sourced from publicly available literature books. The dataset is created for
speech recognition but can be extended to multilingual speech processing
research for both supervised and unsupervised learning approaches. To our
knowledge, this is the first multilingual speech dataset created for Zambian
languages. We exploit pretraining and cross-lingual transfer learning by
finetuning the Wav2Vec2.0 large-scale multilingual pre-trained model to build
end-to-end (E2E) speech recognition models for our baseline models. The dataset
is released publicly under a Creative Commons BY-NC-ND 4.0 license and can be
accessed via https://github.com/unza-speech-lab/zambezi-voice .
