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Parkinson’s disease (PD) is a neurological disorder that affects the communication ability of patients. There is interest in the research community to study acoustic measures that provide objective information to model PD speech. Although there are several studies in the literature that consider different characteristics of Parkinson’s speech like phonation and articulation, there are no studies including...
Information from different bio-signals such as speech, handwriting, and gait have been used to monitor the state of Parkinson's disease (PD) patients, however, all the multimodal bio-signals may not always be available. We propose a method based on multi-view representation learning via generalized canonical correlation analysis (GCCA) for learning a representation of features extracted from handwriting...
Automatic detection of Parkinson's disease (PD) from speech is a basic step towards computer-aided tools supporting the diagnosis and monitoring of the disease. Although several methods have been proposed, their applicability to real-world situations is still unclear. In particular, the effect of acoustic conditions is not well understood. In this paper, the effects on the accuracy of five different...
Parkinson's disease patients develop several impairments related to the speech production process. The deficits of the speech of the patients include reduction in the phonation, articulation, prosody and intelligibility capabilities. Related studies have analyzed the phonation, articulation and prosody of the patients with Parkinson's, while the intelligibility impairments have not been enough evaluated...
Detection of emotion in humans from speech signals is a recent research field. One of the scenarios where this field has been applied is in situations where the human integrity and security are at risk. In this paper we are propossing a set of features based on the Teager energy operator, and several entropy measures obtained from the decomposition signals from discrete wavelet transform to characterize...
The estimation of the fundamental frequency (F0) in speech is a very important task that has been addressed by many researchers. F0 estimation can be used to separate two kind of frames from an utterance, those where the vocal folds vibrate (voiced sounds) and those where not (unvoiced sounds). The methods used to estimate F0 are affected by the presence of additive noise in recordings made in non-controlled...
Parkinsons disease (PD) is a neurodegenerative disorder that affects the coordination and regulation of muscles and limbs, including those responsible of speech production, resulting alterations in voice intelligibility. It is already demonstrated that the constant speech therapy can improve the communication skills of the patients; however, it is required the development of flexible tools able to...
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