In this paper, we proposed a weighted discrete K-nearest neighbor (weighted D-KNN) classification algorithm for detecting and evaluating emotion from Mandarin speech. In the experiments of the emotion recognition, Mandarin emotional speech database used contains five basic emotions, including anger, happiness, sadness, boredom and neutral, and the extracted acoustic features are Mel-Frequency C...

Speech Emotion Recognition (SER) is a common aspect of human-computer interaction and has significant applications in fields such as healthcare, education, elder care. Although researchers have made progress speech emotion feature extraction model identification, they struggled to create an SER system with satisfactory recognition accuracy. To address this issue, we proposed novel algorithm cal...

This paper presents an approach to automatically recognize emotion which children exhibit in an intelligent tutoring system. Emotion recognition can assist the computer agent to adapt its tutorial strategies to improve the efficiency of knowledge transmission. In this study, we detect three emotional classes: confidence, puzzle, and hesitation. Emotion is detected by means of lexical, prosodic,...

The last decade has seen a substantial body of literature on the recognition of emotion from speech. However, in comparison to related speech processing tasks such as Automatic Speech and Speaker Recognition, practically no standardised corpora and test-conditions exist to compare performances under exactly the same conditions. Instead a multiplicity of evaluation strategies employed – such as ...

It has been reported that vocal emotion recognition is challenging for cochlear implant (CI) listeners due to the limited spectral cues with CI devices. As the mechanism of CI, modulation information is provided as a primarily cue. Previous studies have revealed that the modulation components of speech are important for speech intelligibility. However, it is unclear whether modulation informati...