Speech impairments are one of the earliest manifestations in patients with Parkinson’s disease. Particularly, articulation deficits related to the capability of the speaker to start/stop the vibration of the vocal folds have been observed in the …
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 …
Speech disorders are among the most common symptoms in patients with Parkinson’s disease. In recent years, several studies have aimed to analyze speech signals to detect and to monitor the progression of the disease. Most studies have analyzed …
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 …
Different modes of vibration of the vocal folds contribute significantly to the voice quality. The neutral mode phonation, often used in a modal voice, is one against which the other modes can be contrastively described, also called non-modal …
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 …
This study considers phonation and articulation measures to model voice disorders produced by three different pathologies: Laryngeal pathologies (LP), cleft lip and palate (CLP), and Parkinson’s disease (PD). Different speech tasks are considered …
The progression of the disease in Parkinson’s patients is commonly evaluated with the unified Parkinson’s disease rating scale (UPDRS), which contains several items to assess motor and non–motor impairments. The patients develop speech impairments …
This paper presents a system for the automatic detection of hypernasal speech signals based on the combination of two different characterization approaches applied to the five Spanish vowels and two selected words. First one is based on classical …
In the last years, there has a great progress in automatic speech recognition. The challenge now it is not only recognize the semantic content in the speech but also the called 'paralinguistic' aspects of the speech, including the emotions, and the …