Emotional Feature Extraction Based On Phoneme Information for Speech Emotion Recognition

Emotion interaction is an important issue in human robot interaction (HRI). In this paper, we focused on emotion recognition via voice. Generally emotional speech recognition used emotional speech features which are varied as emotion change. However, the emotional speech features changed by not only emotion information but also phoneme information. Therefore we should consider phoneme information when the feature is extracted. So we proposed emotional feature extraction method with considering phoneme information. At first, we evaluated several features such as pitch, energy and formant which are generally used in emotion recognition. Secondly, the features were categorized into emotion reflective features and phoneme dominant features. Finally, emotion reflective features were extracted based on same phoneme information which was classified by phoneme dominant features. This method extracted features which were more sensitive to emotion but less sensitive to phoneme.