abstract
- This paper describes the statistical analysis of a set of features extracted from the speech of sustained vowels of patients with chronic laryngitis and control subjects. The idea is to identify which features can be useful in a classification intelligent system to discriminate between pathologic and healthy voices. The set of features analysed consist in the Jitter, Shimmer Harmonic to Noise Ratio (HNR), Noise to Harmonic Ratio (NHR) and Autocorrelation extracted from the sound of a sustained vowels /a/, /i/ and /u/ in a low, neutral and high tones. The results showed that besides the absolute Jitter, no statistical significance exist between male and female voices, considering the classification between pathologic or healthy. Any of the analysed parameters is likely to be a statistical difference between control and Chronic Laryngitis groups. This is an important information that these features can be used in an intelligent system to classify healthy from Chronic Laryngitis voices.