Voice disorders could increase unhealthy social behavior and voice abuse, and dramatically
affect the patients' quality of life. Therefore, automatic intelligibility detection of pathological …

Pathological speech usually refers to the voice disorders resulting from atypicalities in voice
and/or in the articulatory mechanisms due to disease, illness or other physical problem in …

Automatic detection of pathological voice is a challenging task in speech processing.
Appropriate acoustic cues of voice can be used to differentiate between normal voices and …

Selection of relevant features is important for discriminating speech in detection based ASR
system, thus contributing to the improved performance of the detector. In the context of …

It is commonly acknowledged that word or phoneme intelligibility is an important criterion in
the assessment of the communication efficiency of a pathological speaker. People have …

Pathological speech usually refers to the condition of speech distortion resulting from
atypicalities in voice and/or in the articulatory mechanisms owing to disease, illness or other …

Competitive state-of-the-art automatic pathological speech intelligibility measures typically
rely on regression training on a large number of features, require a large amount of healthy …

Pathological speech usually refers to the condition of speech distortion resulting from
atypicalities in voice and/or in the articulatory mechanisms owing to disease, illness or other …

Intelligibility is widely used to measure the severity of articulatory problems in pathological
speech. Recently, a number of automatic intelligibility assessment tools have been …

Dysarthria is a speech disorder that hinders communication due to difficulties in articulating
words. Detection of dysarthria is important for several reasons as it can be used to develop a …