In the age of artificial intelligence, the best approach to handling huge amounts of data is a
tremendously motivating and hard problem. Among machine learning models, stochastic …

Speech is the most natural way of expressing ourselves as humans. It is only natural then to
extend this communication medium to computer applications. We define speech emotion …

The speech emotion recognition (or, classification) is one of the most challenging topics in
data science. In this work, we introduce a new architecture, which extracts mel-frequency …

Over the past decades, a tremendous amount of research has been done on the use of
machine learning for speech processing applications, especially speech recognition …

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

Emotional state recognition of a speaker is a difficult task for machine learning algorithms
which plays an important role in the field of speech emotion recognition (SER). SER plays a …

The field of machine learning is witnessing its golden era as deep learning slowly becomes
the leader in this domain. Deep learning uses multiple layers to represent the abstractions of …

We aimed at learning deep emotion features to recognize speech emotion. Two
convolutional neural network and long short-term memory (CNN LSTM) networks, one 1D …

Facial expression recognition has been an active area of research over the past few
decades, and it is still challenging due to the high intra-class variation. Traditional …

The advancements in neural networks and the on-demand need for accurate and near real-
time Speech Emotion Recognition (SER) in human–computer interactions make it …