论文标题
比较Covid-19挑战的摘要
A Summary of the ComParE COVID-19 Challenges
论文作者
论文摘要
共同的19日大流行造成了巨大的人道主义和经济损害。来自广泛学科的科学家团队已寻找帮助政府和社区打击疾病的方法。已经探索的机器学习领域的一条途径是进行数字质量测试的前景，可以从受感染者的呼吸道声音中检测到COVID-19。我们介绍了Interspeech 2021计算副语言学挑战的结果：COVID-19-COCH，（CCS）和COVID-19语音（CSS）。
The COVID-19 pandemic has caused massive humanitarian and economic damage. Teams of scientists from a broad range of disciplines have searched for methods to help governments and communities combat the disease. One avenue from the machine learning field which has been explored is the prospect of a digital mass test which can detect COVID-19 from infected individuals' respiratory sounds. We present a summary of the results from the INTERSPEECH 2021 Computational Paralinguistics Challenges: COVID-19 Cough, (CCS) and COVID-19 Speech, (CSS).
