Time–frequency representations of the speech signals provide dynamic information about
how the frequency component changes with time. In order to process this information, deep …

ABSTRACT Background Dysarthric symptoms in Parkinson's disease (PD) vary greatly
across cohorts. Abundant research suggests that such heterogeneity could reflect subject …

Existing works on multimodal affective computing tasks, such as emotion recognition,
generally adopt a two-phase pipeline, first extracting feature representations for each single …

Automatic spoken language identification (LID) is a very important research field in the era of
multilingual voice-command-based human-computer interaction. A front-end LID module …

Aim: This paper introduces Apkinson, a mobile application for motor evaluation and
monitoring of Parkinson's disease patients. Materials & methods: The App is based on …

Stuttering detection and classification are important issues in speech therapy as they could
help therapists track the progression of patients' dysfluencies. This is also an important tool …

Simple Summary A total laryngectomy involves the full and permanent separation of the
upper and lower airways, resulting in the loss of voice and inability to interact vocally. To …

Automatic phonemic transcription tools are useful for low-resource language documentation.
However, due to the lack of training sets, only a tiny fraction of languages have phonemic …

Video emotion recognition aims to infer human emotional states from the audio, visual, and
text modalities. Previous approaches are centered around designing sophisticated fusion …

The automatic prediction of speech intelligibility is a widely known problem in the context of
pathological speech. It has been seen as a growing and viable alternative to perceptual …