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Piano Music Generation with a Text Based Musical Note Representation using LSTM Models

机译:使用LSTM型号的基于文本的音符表示,钢琴音乐生成

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Synthesizing music using Long Short-Term Memory (LSTM) Networks is a widely studied field of research. How the musical notes are abstracted and represented is one of the biggest problems of this process. In this work, a text-based solution, which represents several attributes of musical notes, is proposed as a solution to the mentioned problem. In this notation, numeric representations of the duration and the characteristics of the musical notes in piano pieces are textually combined. The advantages and disadvantages of using the proposed notation are discussed. The proposed method is applied to the created LSTM model, obtained results are discussed. The melodies generated by the trained model are compared to human-made melodies via a survey and the results are shared.
机译:使用长短短期内存(LSTM)网络合成音乐是一种广泛研究的研究领域。 如何抽象和代表的音符是如何实现这一过程的最大问题之一。 在这项工作中,提出了一种基于文本的解决方案,该解决方案表示音符的几个属性,作为提到的问题的解决方案。 在这种表示法中,钢琴件中持续时间和音符特征的数字表示是文本组合的。 讨论了使用该符号的优点和缺点。 该方法应用于所创建的LSTM模型,讨论了得到的结果。 通过调查将受训练模型产生的旋律与人造的旋律进行比较,结果共享结果。

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