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 through the project repository. See
this https URL

Zambezi Voice 为挖掘两个不同语音来源的 Zambian 众所周知，首次推出了适用于 Zambian 语言的多语言语音数据集，可用于监督和非监督的学习方法，同时利用 Wav2Vec2.0 模型进行预训练和跨语言迁移学习，构建出基于端到端的语音识别模型。