Emotion extraction and recognition from music

Music makes our life lovely because it can affect our mental states significantly with its emotional information inside. Different people might be affected differently from the same music when they listening the music in different situation and mental states. However, the common emotion information the music can be agreed even from peoples with quite different background and cultures. An automatic emotion recognition system be proposed for the music by extracting different features from the music and machine learning method learning from common knowledge on emotional state of the trained data in this paper. Firstly, two-channel audio signals are processed, and typical audio features are extracted. Then some other features used for EEG signal analysis are also extracted. Finally, these features are combined and the random forest classifier is used for the classification. The proposed method has been used on a public music dataset for test and the experimental results demonstrate its efficiency when it compare with the state-of-the-art performance in the same dataset.