The speech emotion recognition (SER) field has been active since it became a crucial
feature in advanced Human-Computer Interaction (HCI), and wide real-life applications use …

Speech emotion recognition (SER) as a Machine Learning (ML) problem continues to
garner a significant amount of research interest, especially in the affective computing …

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 …

Speech emotion recognition is a challenging problem because human convey emotions in
subtle and complex ways. For emotion recognition on human speech, one can either extract …

Speech emotion recognition (SER) is a challenging task since it is unclear what kind of
features are able to reflect the characteristics of human emotion from speech. However …

In this paper the task of emotion recognition from speech is considered. Proposed approach
uses deep recurrent neural network trained on a sequence of acoustic features calculated …

In this paper, we show that convolutional neural networks can be directly applied to temporal
low-level acoustic features to identify emotionally salient regions without the need for …

Speech emotion recognition is an important problem with applications as varied as human-
computer interfaces and affective computing. Previous approaches to emotion recognition …

Speech emotion recognition (SER) is a challenging task due to its difficulty in finding proper
representations for emotion embedding in speech. Recently, Convolutional Recurrent …

Abstract Speech Emotion Recognition (SER) is a challengeable task to improve human–
computer interaction. Speech data have different representations, and choosing the …