Emotions are a personal thing: Towards speaker-adaptive emotion recognition

In this paper, we present novel work on speech-based adaptive emotion recognition through addition of speaker-specific information. We propose a two-stage approach of first determining the speaker and then using this information during the emotion recognition process. The proposed technique has been evaluated using five emotional speech databases of different languages using both artificial neural network-based speaker identifier and the ground truth. The addition of speaker-specific information improves the emotion recognition accuracy by up to +10.2%. Moreover, emotion recognition performance scores for all applied databases are improved.