Cough is a primary symptom of most respiratory diseases, and changes in cough characteristics provide valuable information for diagnosing respiratory diseases. The characterization of cough sounds still lacks concrete evidence, which makes it difficult to accurately distinguish between different types of coughs and other sounds. The objective of this research work is to characterize cough sounds with voiced content and cough sounds without voiced content. Further, the cough sound characteristics are compared with the characteristics of speech. The proposed method to achieve this goal utilized spectral roll-off, spectral entropy, spectral flatness, spectral flux, zero crossing rate, spectral centroid, and spectral bandwidth attributes which describe the cough sounds related to the respiratory system, glottal information, and voice model. These attributes are then subjected to statistical analysis using the measures of minimum, maximum, mean, median, and standard deviation. The experimental results show that the mean and frequency distribution of spectral roll-off, spectral centroid, and spectral bandwidth are found to be higher for cough sounds than for speech signals. Spectral flatness levels in cough sounds will rise to 0.22, whereas spectral flux varies between 0.3 and 0.6. The Zero Crossing Rate (ZCR) of most frames of cough sounds is between 0.05 and 0.4. These attributes contribute significant information while characterizing cough sounds.

翻译：咳嗽是大多数呼吸系统疾病的主要症状，咳嗽特征的改变为诊断呼吸系统疾病提供了有价值的信息。然而，咳嗽声音的特征描述仍缺乏具体证据，导致难以准确区分不同咳嗽类型及其他声音。本研究旨在表征包含浊音成分的咳嗽声音与不含浊音成分的咳嗽声音，并将咳嗽声音特征与语音特征进行对比。为实现这一目标，本文采用频谱滚降、频谱熵、频谱平坦度、频谱通量、过零率、频谱质心和频谱带宽等属性来描述与呼吸系统、声门信息及声音模型相关的咳嗽声音特征。随后，利用最小值、最大值、均值、中位数和标准差等统计指标对这些属性进行分析。实验结果表明：咳嗽声音的频谱滚降、频谱质心和频谱带宽的均值及频率分布均高于语音信号；咳嗽声音的频谱平坦度可上升至0.22，频谱通量介于0.3~0.6之间；多数帧的过零率(ZCR)处于0.05~0.4区间。这些属性在咳嗽声音特征描述中提供了重要信息。