Abstract
The classification of voice diseases has many applications in health, disease treatment, and the projection of new medical equipments for diagnosing these pathologies. This work uses the parameters of the glottal signal that are more likely to identify two types of voice disorders: vocal cord nodule and unilateral paralysis of vocal cords. The parameters of the glottal signal are obtained through the known inverse filtering method. The parameters of the glottal signal serve as input to a neural network that classifies into three different groups of speakers: speakers with pathology nodule on one’s vocal cords; with
unilateral vocal cord paralysis; and finally speakers with normal voices. The database is composed of 248 voice recordings containing samples of the three groups mentioned. In this study we have used a larger database for the classification compared with similar studies, and its classification rate is superior to other studies, reaching 95.83%.
unilateral vocal cord paralysis; and finally speakers with normal voices. The database is composed of 248 voice recordings containing samples of the three groups mentioned. In this study we have used a larger database for the classification compared with similar studies, and its classification rate is superior to other studies, reaching 95.83%.
Original language | English |
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Title of host publication | Anais do 10. Congresso Brasileiro de Inteligência Computacional |
Number of pages | 8 |
DOIs | |
State | Published - 2011 |
Event | 10th Brazilian Congress on Computational Intelligence (CBIC’2011) - Ceará, Brazil Duration: 8 Nov 2011 → 11 Nov 2011 |
Congress
Congress | 10th Brazilian Congress on Computational Intelligence (CBIC’2011) |
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Country/Territory | Brazil |
City | Ceará |
Period | 8/11/11 → 11/11/11 |