Acoustic variables in the communication of composer emotional intent.

Music emotion recognition algorithms seek to automatically classify analysed music in terms of the emotion it expresses. Typically these approaches utilise low level acoustical features extracted from the digital music waveform. Research in this area concentrates on the perception of expressed emotion from the user perspective. This approach has received some criticism in that it is limited in terms of unpicking the many facets of emotional communication between the composer and the listener (Miell, MacDonald & Hargreaves 2005), defined in e.g. the lens model of Juslin (2001). The use of acoustical analysis and classification processes can be expanded to include aspects of the musical communication model. This has the potential to shed light on how the composer conveys emotion, and how this is reflected in the acoustical characteristics of the music.