arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2005.09406cs.CLcs.AI
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作为象征音乐表现的嵌入

Embeddings as representation for symbolic music

Universidad EAFIT(EAFIT大学)

Sebastian Garcia-Valencia

摘要:

一种允许以包含音乐意义的方式对音乐进行编码的表示技术将改善任何为计算机音乐任务训练的模型的结果,例如生成更好质量的旋律和和声。自然语言处理领域在寻找捕获单词和句子的语义的方法方面做了大量的工作,并且词嵌入已经成功地显示了这样的任务的能力。在本文中,我们尝试使用嵌入来表示来自数据集的3种不同变体的音符,并分析模型是否可以捕获有用的音乐模式。为此,使用t-SNE技术在投影中可视化得到的嵌入。

英文摘要:

A representation technique that allows encoding music in a way that contains musical meaning would improve the results of any model trained for computer music tasks like generation of melodies and harmonies of better quality. The field of natural language processing has done a lot of work in finding a way to capture the semantic meaning of words and sentences, and word embeddings have successfully shown the capabilities for such a task. In this paper, we experiment with embeddings to represent musical notes from 3 different variations of a dataset and analyze if the model can capture useful musical patterns. To do this, the resulting embeddings are visualized in projections using the t-SNE technique.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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