w—r——i—ti——n—gs———t—imbr—e ——a——n———a——l—ys———is——— ———c——o———m—po———s——i——t———i—on——
———h o m ed——o—w—nl—oa——d—
Timbre can affect our subjective experience of musical dissonance and harmonic progression. To this end, we have developed a set of algorithms to measure roughness (sensory dissonance), and pitch correlation between sonorities, taking into account the effects of timbre and microtonal inflection. We proceed from the work of Richard Parncutt and Ernst Terhardt, extending their algorithms for the psychoacoustic analysis of harmony to include spectral data from actual instrumental sounds. This allows for the study of a much wider variety of timbrally-rich acoustic or electronic sounds which was not possible with the previous algorithms. Further, we generalize these algorithms by working directly with frequency rather than a tempered division of the octave, making them available to the full range of microtonal harmonies. The new algorithms, by yielding different roughness estimates depending on the orchestration of a sonority, confirm our intuitive understanding that orchestration affects sensory dissonance. This package of tools presents rich possibilities for composition and analysis of music that is timbrally-dynamic and microtonally-complex.ci———tat———i—o——n———
J. MacCallum and A. Einbond. Timbre as a psychoacoustic parameter for harmonic analysis and composition. In Proceedings of the International Computer Music Conference. Barcelona, Catalunya. 2005.