Emotion Recognition from Speech Signals and Perception of Music

Abstract

This thesis deals with emotion recognition from speech signals. The feature extraction step shall be improved by looking at the perception of music. In music theory, different pitch intervals (consonant, dissonant) and chords are believed to invoke different feelings in listeners. The question is whether there is a similar mechanism between perception of music and perception of emotional speech. Our research will follow three stages. First, the relationship between speech and music at segmental and supra-segmental levels will be analyzed. Secondly, the encoding of emotions through music shall be investigated. In the third stage, a description of the most common features used for emotion recognition from speech will be provided. We will additionally derive new high-level musical features, which will lead us to an improvement of the recognition rate for the basic spoken emotions.