Emotions are an integral part of human interactions and are significant factors in determining
user satisfaction or customer opinion. speech emotion recognition (SER) modules also play …

As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …

Building on the success of the ADReSS Challenge at Interspeech 2020, which attracted the
participation of 34 teams from across the world, the ADReSSo Challenge targets three …

Automatic speech emotion recognition has been a research hotspot in the field of human-
computer interaction over the past decade. However, due to the lack of research on the …

Abstract Speech Emotion Recognition (SER) can be regarded as a static or dynamic
classification problem, which makes SER an excellent test bed for investigating and …

Work on voice sciences over recent decades has led to a proliferation of acoustic
parameters that are used quite selectively and are not always extracted in a similar fashion …

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

Emotion recognition is challenging due to the emotional gap between emotions and audio-
visual features. Motivated by the powerful feature learning ability of deep neural networks …

Feature selection is a crucial step in the development of a system for identifying emotions in
speech. Recently, the interaction between features generated from the same audio source …

Mood disorders are inherently related to emotion. In particular, the behaviour of people
suffering from mood disorders such as unipolar depression shows a strong temporal …