This paper describes the Ubenwa CryCeleb dataset - a labeled collection of infant cries - and the accompanying CryCeleb 2023 task, which is a public speaker verification challenge based on cry sounds. We released more than 6 hours of manually segmented cry sounds from 786 newborns for academic use, aiming to encourage research in infant cry analysis. The inaugural public competition attracted 59 participants, 11 of whom improved the baseline performance. The top-performing system achieved a significant improvement scoring 25.8% equal error rate, which is still far from the performance of state-of-the-art adult speaker verification systems. Therefore, we believe there is room for further research on this dataset, potentially extending beyond the verification task.

翻译：本文介绍了Ubenwa CryCeleb数据集——一个标注的婴儿哭声集合——以及配套的CryCeleb 2023任务，这是一项基于哭声的公开说话人验证挑战。我们发布了来自786名新生儿的超过6小时手动分割的哭声数据，供学术使用，旨在促进婴儿哭声分析的研究。该首次公开竞赛吸引了59名参与者，其中11人提升了基线性能。表现最佳的系统取得了显著改进，其等错误率为25.8%，但仍远低于当前成人说话人验证系统的性能。因此，我们认为该数据集存在进一步研究的空间，可能超出验证任务本身。