Automatic identification of dysprosody in idiopathic Parkinson's disease

• Published in: Biomedical signal processing and control 2015-03, Vol.17, p.47-54
• Main Authors: Bandini, A., Giovannelli, F., Orlandi, S., Barbagallo, S.D., Cincotta, M., Vanni, P., Chiaramonti, R., Borgheresi, A., Zaccara, G., Manfredi, C.
• Format: Article
• Language: English
• Subjects: Automatic acoustic analysis; Dysprosody; Objective parameters; Parkinson's disease
• ISSN: 1746-8094
• DOI: 10.1016/j.bspc.2014.07.006

•We analyze dysprosody in patients with idiopathic Parkinson's disease using a sentence repetition task.•We perform an automatic analysis of speech signals.•PD patients exhibit longer pauses between each sentence repetition.•PD patients show a lower percentage of “speech time” during a whole repetition period. Parkinson's disease (PD) involves impairments of voice and speech (hypokinetic dysarthria). Dysprosody is one of the most common features of PD speech that includes alterations of rhythm and velocity of articulation. The aim of this study is the evaluation of dysprosody patterns in Parkinsonian patients during a sentence repetition task by means of a fully automated tool. Twenty PD patients (14 male and 6 female) and 19 healthy controls (9 male and 10 female) were tested. Results show significant differences between the two groups as far as the time interval between each sentence repetition (Tinter), the percent of speech time with respect to sentence duration (D%) and the Net Speech Rate (NSR – defined as the number of syllables of the sentence divided by the effective speech time) are concerned. In particular, Tinter is larger in PD patients while D% is higher in the control group. These results show that PD patients may exhibit longer pauses between each sentence repetition and a lower percentage of “speech time” during a whole repetition period. Thus, the decrease of D% leads to an increase of NSR. Other acoustic parameters (noise and F0 variability) did not show any significant difference. This study confirms that speech in PD patients is characterized by short rushes followed by unorthodox pauses. These results may lead to the development of a system for the automatic acoustic analysis which could significantly reduce the processing time in particular during pre-processing, that to date is a time-consuming and operator-dependent step especially in case of recordings of long duration.