AI Harmonizer: Expanding Vocal Expression with a Generative Neurosymbolic Music AI System
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866911018891870208 |
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| author | Blanchard, Lancelot Holt, Cameron Paradiso, Joseph A. |
| author_facet | Blanchard, Lancelot Holt, Cameron Paradiso, Joseph A. |
| contents | Vocals harmonizers are powerful tools to help solo vocalists enrich their melodies with harmonically supportive voices. These tools exist in various forms, from commercially available pedals and software to custom-built systems, each employing different methods to generate harmonies. Traditional harmonizers often require users to manually specify a key or tonal center, while others allow pitch selection via an external keyboard-both approaches demanding some degree of musical expertise. The AI Harmonizer introduces a novel approach by autonomously generating musically coherent four-part harmonies without requiring prior harmonic input from the user. By integrating state-of-the-art generative AI techniques for pitch detection and voice modeling with custom-trained symbolic music models, our system arranges any vocal melody into rich choral textures. In this paper, we present our methods, explore potential applications in performance and composition, and discuss future directions for real-time implementations. While our system currently operates offline, we believe it represents a significant step toward AI-assisted vocal performance and expressive musical augmentation. We release our implementation on GitHub. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_18143 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AI Harmonizer: Expanding Vocal Expression with a Generative Neurosymbolic Music AI System Blanchard, Lancelot Holt, Cameron Paradiso, Joseph A. Human-Computer Interaction Artificial Intelligence Sound Audio and Speech Processing H.5.5 Vocals harmonizers are powerful tools to help solo vocalists enrich their melodies with harmonically supportive voices. These tools exist in various forms, from commercially available pedals and software to custom-built systems, each employing different methods to generate harmonies. Traditional harmonizers often require users to manually specify a key or tonal center, while others allow pitch selection via an external keyboard-both approaches demanding some degree of musical expertise. The AI Harmonizer introduces a novel approach by autonomously generating musically coherent four-part harmonies without requiring prior harmonic input from the user. By integrating state-of-the-art generative AI techniques for pitch detection and voice modeling with custom-trained symbolic music models, our system arranges any vocal melody into rich choral textures. In this paper, we present our methods, explore potential applications in performance and composition, and discuss future directions for real-time implementations. While our system currently operates offline, we believe it represents a significant step toward AI-assisted vocal performance and expressive musical augmentation. We release our implementation on GitHub. |
| title | AI Harmonizer: Expanding Vocal Expression with a Generative Neurosymbolic Music AI System |
| topic | Human-Computer Interaction Artificial Intelligence Sound Audio and Speech Processing H.5.5 |
| url | https://arxiv.org/abs/2506.18143 |