Journal
TEXT, SPEECH, AND DIALOGUE, TSD 2017
Volume 10415, Issue -, Pages 411-419Publisher
SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-319-64206-2_46
Keywords
Parkinson's disease; Phonation; Articulation; Prosody
Funding
- Portuguese national funds through Fundacao para a Ciencia e a Tecnologia (FCT) [SFRH/BD/97187/2013, UID/CEC/50021/2013, CMUP-ERI/TIC/0033/2014]
- Fundação para a Ciência e a Tecnologia [CMUP-ERI/TIC/0033/2014, SFRH/BD/97187/2013] Funding Source: FCT
Ask authors/readers for more resources
Parkinson's disease (PD) is the second most common neurodegenerative disorder of mid-to-late life after Alzheimer's disease. During the progression of the disease, most individuals with PD report impairments in speech due to deficits in phonation, articulation, prosody, and fluency. In the literature, several studies perform the automatic classification of speech of people with PD considering various types of acoustic information extracted from different speech tasks. Nevertheless, it is unclear which tasks are more important for an automatic classification of the disease. In this work, we compare the discriminant capabilities of eight verbal tasks designed to capture the major symptoms affecting speech. To this end, we introduce a new database of Portuguese speakers consisting of 65 healthy control and 75 PD subjects. For each task, an automatic classifier is built using feature sets and modeling approaches in compliance with the current state of the art. Experimental results permit to identify reading aloud prosodic sentences and story-telling tasks as the most useful for the automatic detection of PD.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available