In recent years, the rapid development of sensors and information technology has made it
possible for machines to recognize and analyze human emotions. Emotion recognition is an …

Multimodal machine learning (MML) is a tempting multidisciplinary research area where
heterogeneous data from multiple modalities and machine learning (ML) are combined to …

Conversational emotion recognition (CER) is an important research topic in human-
computer interactions. Although recent advancements in transformer-based cross-modal …

The proliferation of mobile devices and the rapid development of information and
communication technologies (ICT) have seen increasingly large volume and variety of data …

In this article, K-meansclustering-based Kernel canonical correlation analysis algorithm is
proposed for multimodal emotion recognition in human–robot interaction (HRI). The …

Multi-modal conversation emotion recognition (MCER) aims to recognize and track the
speaker's emotional state using text, speech, and visual information in the conversation …

This paper presents a multimodal emotion recognition system, which is based on the
analysis of audio and visual cues. From the audio channel, Mel-Frequency Cepstral …

Emotion is a human attitude experience and corresponding behavioral response to
objective things. Effective emotion recognition is important for the intelligence and …

Multimodal multi-label emotion recognition (MMER) is a vital yet challenging task in affective
computing. Despite significant progress in previous works, there are three limitations:(i) …

Robots must be able to recognize human emotions to improve the human-robot interaction
(HRI). This study proposes an emotion recognition system for a humanoid robot. The robot is …