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

Emotion recognition has recently attracted extensive interest due to its significant
applications to human-computer interaction. The expression of human emotion depends on …

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 …

We present a new implementation of emotion recognition from the para-lingual information
in the speech, based on a deep neural network, applied directly to spectrograms. This new …

This monograph provides an overview of general deep learning methodology and its
applications to a variety of signal and information processing tasks. The application areas …

As an essential way of human emotional behavior understanding, speech emotion
recognition (SER) has attracted a great deal of attention in human-centered signal …

Deep learning systems, such as Convolutional Neural Networks (CNNs), can infer a
hierarchical representation of input data that facilitates categorization. In this paper, we …

Speech emotion recognition (SER) plays a significant role in human–machine interaction.
Emotion recognition from speech and its precise classification is a challenging task because …

Abstract After 2007–2008 crisis, it is clear that corporate credit scoring is becoming a key
role in credit risk management. In this paper, we investigate the performances of credit …

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 …