This paper explores the idea of utilising Long Short-Term Memory neural networks (LSTMNN) for the generation of musical sequences in ABC notation. The proposed approach takes ABC notations from the Nottingham dataset and encodes it to beefed as input for the neural networks. The primary objective is to input the neural networks with an arbitrary note, let the network process and augment a sequence based on the note until a good piece of music is produced. Multiple tunings have been done to amend the parameters of the network for optimal generation. The output is assessed on the basis of rhythm, harmony, and grammar accuracy.
翻译:本文件探讨了利用长期短期内存神经网络(LSTMNN)来生成ABC符号中的音乐序列的想法。提议的方法从诺丁汉数据集中提取ABC符号并将其编码为神经网络的输入。主要目的是用一个任意的注解输入神经网络,让网络进程并增加一个基于音符的序列,直到产生一个好的音乐。已经做了多项调整,以修改网络参数,实现最佳生成。产出根据节奏、和谐和语法精确度进行评估。