标题： 赞比西语音：用于赞比亚语言的多语言语音语料库 显示英文标题

标题： Zambezi Voice: A Multilingual Speech Corpus for Zambian Languages

摘要： 这项工作介绍了赞比西语音，这是一个针对赞比亚语言的开源多语言语音资源。 它包含两个数据集集合：未标记的广播新闻和访谈节目音频记录（160小时）以及标记数据（超过80小时），这些数据包括从公开可用的文学书籍中获取文本录制的朗读语音。 该数据集用于语音识别，但可以扩展到针对监督和非监督学习方法的多语言语音处理研究。 据我们所知，这是首个为赞比亚语言创建的多语言语音数据集。 我们通过微调Wav2Vec2.0大规模多语言预训练模型来构建端到端（E2E）语音识别模型作为我们的基线模型，从而利用预训练和跨语言迁移学习。 该数据集在Creative Commons BY-NC-ND 4.0许可下公开发布，可通过https://github.com/unza-speech-lab/zambezi-voice访问。 显示英文摘要

摘要： 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 .