Insights on Harmonic Tones from a Generative Music Experiment
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866914568192655360 |
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| author | Deruty, Emmanuel Grachten, Maarten |
| author_facet | Deruty, Emmanuel Grachten, Maarten |
| contents | The ultimate purpose of generative music AI is music production. The studio-lab, a social form within the art-science branch of cross-disciplinarity, is a way to advance music production with AI music models. During a studio-lab experiment involving researchers, music producers, and an AI model for music generating bass-like audio, it was observed that the producers used the model's output to convey two or more pitches with a single harmonic complex tone, which in turn revealed that the model had learned to generate structured and coherent simultaneous melodic lines using monophonic sequences of harmonic complex tones. These findings prompt a reconsideration of the long-standing debate on whether humans can perceive harmonics as distinct pitches and highlight how generative AI can not only enhance musical creativity but also contribute to a deeper understanding of music. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_07073 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Insights on Harmonic Tones from a Generative Music Experiment Deruty, Emmanuel Grachten, Maarten Sound Human-Computer Interaction Audio and Speech Processing 68T01 J.5 The ultimate purpose of generative music AI is music production. The studio-lab, a social form within the art-science branch of cross-disciplinarity, is a way to advance music production with AI music models. During a studio-lab experiment involving researchers, music producers, and an AI model for music generating bass-like audio, it was observed that the producers used the model's output to convey two or more pitches with a single harmonic complex tone, which in turn revealed that the model had learned to generate structured and coherent simultaneous melodic lines using monophonic sequences of harmonic complex tones. These findings prompt a reconsideration of the long-standing debate on whether humans can perceive harmonics as distinct pitches and highlight how generative AI can not only enhance musical creativity but also contribute to a deeper understanding of music. |
| title | Insights on Harmonic Tones from a Generative Music Experiment |
| topic | Sound Human-Computer Interaction Audio and Speech Processing 68T01 J.5 |
| url | https://arxiv.org/abs/2506.07073 |