Background Digital phenoty** is the use of data from smartphones and wearables
collected in situ for capturing a digital expression of human behaviors. Digital phenoty** …

Automatic emotion recognition is the process of identifying human emotion from signals
such as facial expression, speech, and text. Collecting and labeling such signals is often …

Traditionally, speech emotion recognition (SER) research has relied on manually
handcrafted acoustic features using feature engineering. However, the design of …

Automatic speech emotion recognition provides computers with critical context to enable
user understanding. While methods trained and tested within the same dataset have been …

Many mobile applications and virtual conversational agents now aim to recognize and adapt
to emotions. To enable this, data are transmitted from users' devices and stored on central …

Quantifying neurological disorders from voice is a rapidly growing field of research and
holds promise for unobtrusive and large-scale disorder monitoring. The data recording setup …

Social impairment is a cardinal feature of schizophrenia spectrum disorders (SZ). Smaller
social network size, diminished social skills, and loneliness are highly prevalent. Existing …

Depression detection from speech continues to attract significant research attention but
remains a major challenge, particularly when the speech is acquired from diverse …

The substantial growth of Internet-of-Things technology and the ubiquity of smartphone
devices has increased the public and industry focus on speech emotion recognition (SER) …

The massive and growing burden imposed on modern society by depression has motivated
investigations into early detection through automated, scalable and non-invasive methods …