Towards Modeling Texture in Symbolic Data

Studying texture is a part of many musicological analyses. The change of texture plays an important role in the cognition of musical structures. Texture is a feature commonly used to analyze musical audio data, but it is rarely taken into account in symbolic studies. We propose to formalize the texture in classical Western instrumental music as melody and accompaniment layers, and provide an algorithm able to detect homorhythmic layers in polyphonic data where voices are not separated. We present an evaluation of these methods for parallel motions against a ground truth analysis of ten instrumental pieces, including the first movements of the six quatuors op. 33 by Haydn.