In this paper, a novel approach, which is based on attention guided 3D convolutional neural
networks (CNN)-long short-term memory (LSTM) model, is proposed for speech based …

Human-Robot interactions involve human intentions and human emotion. After the
evolvement of positive psychology, the psychological research has a tremendous …

Emotion recognition from speech data is an active and emerging area of research that plays
an important role in numerous applications, such as robotics, virtual reality, behavior …

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 …

Precise recognition of emotion from speech signals aids in enhancing human–computer
interaction (HCI). The performance of a speech emotion recognition (SER) system depends …

Emotion information from speech can effectively help robots understand speaker's intentions
in natural human-robot interaction. The human auditory system can easily track temporal …

Artificial intelligence, deep learning, and machine learning are dominant sources to use in
order to make a system smarter. Nowadays, the smart speech emotion recognition (SER) …

Speech is the most dominant source of communication among humans, and it is an efficient
way for human–computer interaction (HCI) to exchange information. Nowadays, speech …

Speech emotion recognition (SER) plays a vital role in human–machine interaction. A large
number of SER schemes have been anticipated over the last decade. However, the …

We propose a speech-emotion recognition (SER) model with an “attention-long Long Short-
Term Memory (LSTM)-attention” component to combine IS09, a commonly used feature for …