(MIR) is an interdisciplinary science aimed to studying the processes, systems and knowledge representations required for retrieving information from music. This music can be in symbolic format (e.g., a MIDI file), in audio format (e.g. an mp3 file), or in vector format (e.g., a scanned score). MIR research takes advantage of technologies and knowledge derived from signal processing, machine learning, music cognition, database management, human-computer interaction, music archiving or sociology of music.
Published in Chapter:
Automatic Detection of Emotion in Music: Interaction with Emotionally Sensitive Machines
Cyril Laurier (Universitat Pompeu Fabra, Spain) and Perfecto Herrera (Universitat Pompeu Fabra, Spain)
Copyright: © 2009
|Pages: 25
DOI: 10.4018/978-1-60566-354-8.ch002
Abstract
Creating emotionally sensitive machines will significantly enhance the interaction between humans and machines. In this chapter we focus on enabling this ability for music. Music is extremely powerful to induce emotions. If machines can somehow apprehend emotions in music, it gives them a relevant competence to communicate with humans. In this chapter we review the theories of music and emotions. We detail different representations of musical emotions from the literature, together with related musical features. Then, we focus on techniques to detect the emotion in music from audio content. As a proof of concept, we detail a machine learning method to build such a system. We also review the current state of the art results, provide evaluations and give some insights into the possible applications and future trends of these techniques.