  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.
