Speech emotion recognition (SER) is traditionally performed using merely acoustic
information. Acoustic features, commonly are extracted per frame, are mapped into emotion …

The Coronavirus (COVID-19) pandemic has been the research focus world-wide in the year
2020. Several efforts, from collection of COVID-19 patients' data to screening them for the …

As emotions play a central role in human communication, automatic emotion recognition has
attracted increasing attention in the last two decades. While multimodal systems enjoy high …

This paper describes deep learning approaches for the Mask and Breathing Sub-
Challenges (SCs), which are addressed by the INTERSPEECH 2020 Computational …

Bipolar disorder is a mental health disorder that causes mood swings that range from
depression to mania. Clinical diagnosis of bipolar disorder is based on patient interviews …

Computational technologies have revolutionized the archival sciences field, prompting new
approaches to process the extensive data in these collections. Automatic speech recognition …

Commonly adapted design of emotional corpora includes multiple annotations for the same
instance from several annotators. Most of the previous studies assume the ground truth to be …

Speech timing and non-speech regions (here referred to as “silence”), often play a critical
role in the perception of spoken language. Silence represents an important paralinguistic …

This paper presents a novel bimodal speech emotion recognition system based on analysis
of acoustic and linguistic information. We propose a novel decision-level fusion strategy that …

Speech Emotion Recognition (SER) is one of the essential perceptual methods of humans in
understanding the situation and how to interact with others, therefore, in recent years, it has …