Emotion recognition from speech signals is an important but challenging component of
Human-Computer Interaction (HCI). In the literature of speech emotion recognition (SER) …

Background Human emotions greatly affect the actions of a person. The automated emotion
recognition has applications in multiple domains such as health care, e-learning …

Emotion recognition datasets are relatively small, making the use of the more sophisticated
deep learning approaches challenging. In this work, we propose a transfer learning method …

One of the main challenges facing the current approaches of speech emotion recognition is
the lack of a dataset large enough to train the currently available deep learning models …

Deep learning methods haverevolutionized speech recognition, image recognition, and
natural language processing since 2010. Each of these tasks involves a single modality in …

Speech emotion recognition is a vital and challenging task that the feature extraction plays a
significant role in the SER performance. With the development of deep learning, we put our …

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 …

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

Nowadays emotion recognition from speech (SER) is a demanding research area for
researchers because of its wide real-life applications. There are many challenges for SER …

Recognizing human emotions by machines is a complex task. Deep learning models
attempt to automate this process by rendering machines to exhibit learning capabilities …