{"title":"The Data-Driven Algorithmic Composer","authors":"J. Fitzpatrick, Flaithrí Neff","doi":"10.1145/3123514.3123549","DOIUrl":null,"url":null,"abstract":"The Data-Driven Algorithmic Composer (D-DAC) is an application designed to output data-driven algorithmically composed music via MIDI. The application requires input data to be in tab-separated format to be compatible. Each dataset results in a unique piece of music that remains consistent with each iteration of the application. The only varying elements between each iteration of the same dataset are factors defined by the user: tempo, scale, and intervals between rows. Each measure of the melody, harmony and bassline is derived from each row of the dataset. By utilizing this non-random algorithmic application, users can create a unique and predefined musical iteration of their dataset. The overall aim of the D-DAC is to inspire musical creativity from scientific data and encourage the sharing of datasets between various research communities.","PeriodicalId":282371,"journal":{"name":"Proceedings of the 12th International Audio Mostly Conference on Augmented and Participatory Sound and Music Experiences","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 12th International Audio Mostly Conference on Augmented and Participatory Sound and Music Experiences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3123514.3123549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The Data-Driven Algorithmic Composer (D-DAC) is an application designed to output data-driven algorithmically composed music via MIDI. The application requires input data to be in tab-separated format to be compatible. Each dataset results in a unique piece of music that remains consistent with each iteration of the application. The only varying elements between each iteration of the same dataset are factors defined by the user: tempo, scale, and intervals between rows. Each measure of the melody, harmony and bassline is derived from each row of the dataset. By utilizing this non-random algorithmic application, users can create a unique and predefined musical iteration of their dataset. The overall aim of the D-DAC is to inspire musical creativity from scientific data and encourage the sharing of datasets between various research communities.