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 …

During the last decade, Speech Emotion Recognition (SER) has emerged as an integral
component within Human-computer Interaction (HCI) and other high-end speech processing …

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 …

Speech emotion recognition is a challenging task, and extensive reliance has been placed
on models that use audio features in building well-performing classifiers. In this paper, we …

Abstract Speech Emotion Recognition (SER) can be regarded as a static or dynamic
classification problem, which makes SER an excellent test bed for investigating and …

Speech is an effective medium to express emotions and attitude through language. Finding
the emotional content from a speech signal and identify the emotions from the speech …

Speech emotion recognition is a challenging problem partly because it is unclear what
features are effective for the task. In this paper we propose to utilize deep neural networks …

The detection and monitoring of emotions are important in various applications, eg, to
enable naturalistic and personalised human-robot interaction. Emotion detection often …

Speech emotion recognition (SER) classifies speech into emotion categories such as:
Happy, Angry, Sad and Neutral. Recently, deep learning has been applied to the SER task …

Accurately recognizing emotion from speech is a necessary yet challenging task due to the
variability in speech and emotion. In this paper, we propose a speech emotion recognition …