In-depth analysis of music structure as a text network
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866929196036521984 |
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| author | Tsai, Ping-Rui Chou, Yen-Ting Wang, Nathan-Christopher Chen, Hui-Ling Huang, Hong-Yue Luo, Zih-Jia Hong, Tzay-Ming |
| author_facet | Tsai, Ping-Rui Chou, Yen-Ting Wang, Nathan-Christopher Chen, Hui-Ling Huang, Hong-Yue Luo, Zih-Jia Hong, Tzay-Ming |
| contents | Music, enchanting and poetic, permeates every corner of human civilization. Although music is not unfamiliar to people, our understanding of its essence remains limited, and there is still no universally accepted scientific description. This is primarily due to music being regarded as a product of both reason and emotion, making it difficult to define. In this article, we focus on the fundamental elements of music and construct an evolutionary network from the perspective of music as a natural language, aligning with the statistical characteristics of texts. Through this approach, we aim to comprehend the structural differences in music across different periods, enabling a more scientific exploration of music. Relying on the advantages of structuralism, we can concentrate on the relationships and order between the physical elements of music, rather than getting entangled in the blurred boundaries of science and philosophy. The scientific framework we present not only conforms to past conclusions in music, but also serves as a bridge that connects music to natural language processing and knowledge graphs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_13631 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | In-depth analysis of music structure as a text network Tsai, Ping-Rui Chou, Yen-Ting Wang, Nathan-Christopher Chen, Hui-Ling Huang, Hong-Yue Luo, Zih-Jia Hong, Tzay-Ming Sound Artificial Intelligence Computation and Language Audio and Speech Processing Music, enchanting and poetic, permeates every corner of human civilization. Although music is not unfamiliar to people, our understanding of its essence remains limited, and there is still no universally accepted scientific description. This is primarily due to music being regarded as a product of both reason and emotion, making it difficult to define. In this article, we focus on the fundamental elements of music and construct an evolutionary network from the perspective of music as a natural language, aligning with the statistical characteristics of texts. Through this approach, we aim to comprehend the structural differences in music across different periods, enabling a more scientific exploration of music. Relying on the advantages of structuralism, we can concentrate on the relationships and order between the physical elements of music, rather than getting entangled in the blurred boundaries of science and philosophy. The scientific framework we present not only conforms to past conclusions in music, but also serves as a bridge that connects music to natural language processing and knowledge graphs. |
| title | In-depth analysis of music structure as a text network |
| topic | Sound Artificial Intelligence Computation and Language Audio and Speech Processing |
| url | https://arxiv.org/abs/2303.13631 |