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

Conversational systems have come a long way since their inception in the 1960s. After
decades of research and development, we have seen progress from Eliza and Parry in the …

User emotional status recognition is becoming a key feature in advanced Human Computer
Interfaces (HCI). A key source of emotional information is the spoken expression, which may …

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 …

This paper presents a speech emotion recognition system using a recurrent neural network
(RNN) model trained by an efficient learning algorithm. The proposed system takes into …

We present the MSP-IMPROV corpus, a multimodal emotional database, where the goal is
to have control over lexical content and emotion while also promoting naturalness in the …

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 …

Automatic emotion recognition systems predict high-level affective content from low-level
human-centered signal cues. These systems have seen great improvements in classification …

Emotion analysis and recognition has become an interesting topic of research among the
computer vision research community. In this paper, we first present the emoF-BVP database …

Speech Emotion Recognition (SER) refers to the use of machines to recognize the emotions
of a speaker from his (or her) speech. SER benefits Human-Computer Interaction (HCI). But …