Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
In recent years, the rapid advances in machine learning (ML) and information fusion has
made it possible to endow machines/computers with the ability of emotion understanding …
made it possible to endow machines/computers with the ability of emotion understanding …
A survey on deep learning for multimodal data fusion
With the wide deployments of heterogeneous networks, huge amounts of data with
characteristics of high volume, high variety, high velocity, and high veracity are generated …
characteristics of high volume, high variety, high velocity, and high veracity are generated …
A review of affective computing: From unimodal analysis to multimodal fusion
Affective computing is an emerging interdisciplinary research field bringing together
researchers and practitioners from various fields, ranging from artificial intelligence, natural …
researchers and practitioners from various fields, ranging from artificial intelligence, natural …
Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges
Abstract Body Sensor Networks (BSNs) have emerged as a revolutionary technology in
many application domains in health-care, fitness, smart cities, and many other compelling …
many application domains in health-care, fitness, smart cities, and many other compelling …
Hybrid contrastive learning of tri-modal representation for multimodal sentiment analysis
The wide application of smart devices enables the availability of multimodal data, which can
be utilized in many tasks. In the field of multimodal sentiment analysis, most previous works …
be utilized in many tasks. In the field of multimodal sentiment analysis, most previous works …
Mosi: multimodal corpus of sentiment intensity and subjectivity analysis in online opinion videos
People are sharing their opinions, stories and reviews through online video sharing
websites every day. Studying sentiment and subjectivity in these opinion videos is …
websites every day. Studying sentiment and subjectivity in these opinion videos is …
A review and meta-analysis of multimodal affect detection systems
SK D'mello, J Kory - ACM computing surveys (CSUR), 2015 - dl.acm.org
Affect detection is an important pattern recognition problem that has inspired researchers
from several areas. The field is in need of a systematic review due to the recent influx of …
from several areas. The field is in need of a systematic review due to the recent influx of …
Learning affective features with a hybrid deep model for audio–visual emotion recognition
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 …
visual features. Motivated by the powerful feature learning ability of deep neural networks …
Emotion recognition from multiple modalities: Fundamentals and methodologies
Humans are emotional creatures. Multiple modalities are often involved when we express
emotions, whether we do so explicitly (such as through facial expression and speech) or …
emotions, whether we do so explicitly (such as through facial expression and speech) or …
A multimodal hierarchical approach to speech emotion recognition from audio and text
Speech emotion recognition (SER) plays a crucial role in improving the quality of man–
machine interfaces in various fields like distance learning, medical science, virtual …
machine interfaces in various fields like distance learning, medical science, virtual …