Authors:
João Paulo Teixeira
1
;
2
;
Joana Fernandes
1
;
Filipe Teixeira
1
and
Paula Odete Fernandes
3
;
1
;
2
Affiliations:
1
Polytechnic Institute of Bragança, Portugal
;
2
Applied Management Research Unit (UNIAG), Portugal
;
3
Research Unit in Business Sciences (NECE-UBI), Portugal
Keyword(s):
Chronic Laryngitis, Acoustic Analysis, Jitter, Shimmer, HNR, NHR, Auto Correlation.
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.