SPEECH EMOTION RECOGNITION

Speech Emotion Recognition Using Scalogram Based Deep Structure

Speech Emotion Recognition (SER) is an important part of speech-based Human-Computer Interface (HCI) applications. Previous SER methods rely on the extraction of features and training an appropriate classifier. However, most of those features can be affected by emotionally irrelevant factors such as gender, speaking styles and environment. Here, an SER method has been proposed based on a concat...

Emotion Recognition from Speech

This paper proposes the classification of emotions based on spectral features using the Gaussian Mixture Model as the classifier. The performance of the Gaussian Mixture Model has been evaluated for two types of databases – acted and reallife speech corpuses. The model has also been evaluated for the variation in its performance based on the speaker, gender of the speaker and the number of the ...

Speech Emotion Recognition

Emotion recognition using imperfect speech recognition

This paper investigates the use of speech-to-text methods for assigning an emotion class to a given speech utterance. Previous work shows that an emotion extracted from text can convey complementary evidence to the information extracted by classifiers based on spectral, or other non-linguistic features. As speech-to-text usually presents significantly more computational effort, in this study we...

Emotion Recognition in Spontaneous Speech

Automatic detection of emotions has been evaluated using standard Mel-frequency Cepstral Coefficients, MFCCs, and a variant, MFCC-low, that is calculated between 20 and 300 Hz in order to model pitch. Plain pitch features have been used as well. These acoustic features have all been modeled by Gaussian mixture models, GMMs, on the frame level. The method has been tested on two different corpora...