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 …

Despite advances in antimicrobial and anti-inflammatory therapies, inflammation and its
consequences still remain a significant problem in medicine. Acute inflammatory responses …

Receiving an accurate emotional response from robots has been a challenging task for
researchers for the past few years. With the advancements in technology, robots like service …

While speech emotion recognition (SER) has been an active research field since the last
three decades, the techniques that deal with the natural environment have only emerged in …

The two-layer fuzzy multiple random forest (TLFMRF) is proposed for speech emotion
recognition. When recognizing speech emotion, there are usually some problems. One is …

With the advancement of human-computer interaction, robotics, and especially humanoid
robots, there is an increasing trend for human-to-human communications over online …

The majority of existing speech emotion recognition research focuses on automatic emotion
detection using training and testing data from same corpus collected under the same …

In critical applications, such as medical diagnosis, security related systems, and so on, the
cost or risk of action taking based on incorrect classification can be very high. Hence …

Despite the recent advancement in speech emotion recognition (SER) within a single corpus
setting, the performance of these SER systems degrades significantly for cross-corpus and …

Speech emotion recognition (SER) as a Machine Learning (ML) problem continues to
garner a significant amount of research interest, especially in the affective computing …