Musical sequence comparison for melodic and rhythmic similarities

Kadota, T; Hirao, Masahiro; Ishino, Akira; Takeda, Masayuki; Shinohara, Ayumi; Fumihiro, Matsuo

doi:10.1109/spire.2001.989744

Cited by 5 publications

(1 citation statement)

References 15 publications

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“…where Melody Fitness i is the fitness value of score information in the melody part of the ith variation referring to [11], and Impression Fitness i is the fitness value of impressions on the ith variation [5]. Impression values of variations are estimated by MNN models.…”

Section: Calculation Of Fitness Value [5]mentioning

confidence: 99%

Generation of Variations on Theme Music Based on Impressions of Story ScenesConsidering Human′s Feeling of Music and Stories

Ishizuka

Onisawa

2007

International Journal of Computer Games Technology

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This paper describes a system which generates variations on theme music fitting to story scenes represented by texts and/or pictures. Inputs to the present system are original theme music and numerical information on given story scenes. The present system varies melodies, tempos, tones, tonalities, and accompaniments of given theme music based on impressions of story scenes. Genetic algorithms (GAs) using modular neural network (MNN) models as fitness functions are applied to music generation in order to reflect user's feeling of music and stories. The present system adjusts MNN models for each user on line. This paper also describes the evaluation experiments to confirm whether the generated variations on theme music reflect impressions of story scenes appropriately or not.

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Section: Calculation Of Fitness Value [5]mentioning

confidence: 99%