论文标题
检测和分析野外自发的口腔癌演讲
Detecting and analysing spontaneous oral cancer speech in the wild
论文作者
论文摘要
口腔癌的言论是一种每年影响全球超过50万人的疾病。迄今为止，口腔癌言语的分析集中在阅读语音上。在本文中，我们1）存在和2）分析从YouTube收集的三个小时自发的口腔癌语音数据集。 3）我们为该数据集的口腔癌语音检测任务设置了基准。对这些可解释的机器学习基线的分析表明，助剂和停止辅音是自发口腔癌语音检测的最重要指标。
Oral cancer speech is a disease which impacts more than half a million people worldwide every year. Analysis of oral cancer speech has so far focused on read speech. In this paper, we 1) present and 2) analyse a three-hour long spontaneous oral cancer speech dataset collected from YouTube. 3) We set baselines for an oral cancer speech detection task on this dataset. The analysis of these explainable machine learning baselines shows that sibilants and stop consonants are the most important indicators for spontaneous oral cancer speech detection.
