Retargeting Expressive Musical Style from Classical Music Recordings Using a Support Vector Machine

摘要

A method for retargeting musical style from audio recordings to MIDI is proposed. First the audio file is divided into phrases according to cadence, pitch pattern, and local energy. The phrases are then trained with SVM to obtain the style parameters, including dynamics, tempo, and articulation. The extracted performance style is then applied to a raw MIDI note list to make it expressive. Experiments show that this method reproduces a performer's style with a high level of correlation to real performances.