Towards efficient real-time generation of detectable musical macrostructure

可检测的大尺度音乐结构的有效生成是商业视听应用和创造性音乐制作所需要的。但计算机对音乐的调解集中在其他地方：声音合成和排序，编辑，混合和记谱。我将应用计算过程，如处理进化中的遗传信息块，以产生大规模的音乐结构。我将控制分割;内部片段的框架;空间化;以及可分离音乐流的叠加。专家的认知评估所产生的结构将进行调查，分割理论，流及其与表达和影响的关系发展和测试。

Efficient generation of detectable large scale musical structure is needed for commercial audiovisual applications, and for creative music making. But computer mediation of music has focused elsewhere: on sound synthesis and sequencing, editing, mixing and notation. I will apply computational processes like the handling of chunks of genetic information in evolution, to generate large scale musical structure. I will control segmentation; framing of internal segments; spatialisation; and the overlaying of separable musical streams. Expert cognitive assessment of the resultant structures will be investigated, and theories of segmentation, streaming and their relationships with expression and affect developed and tested.