AI Harmonizer: Expanding Vocal Expression with a Generative Neurosymbolic Music AI System

Lancelot Blanchard, Cameron Holt, and Joseph Paradiso

Proceedings of the International Conference on New Interfaces for Musical Expression

Abstract

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.

Citation

Lancelot Blanchard, Cameron Holt, and Joseph Paradiso. 2025. AI Harmonizer: Expanding Vocal Expression with a Generative Neurosymbolic Music AI System. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.15698966 [PDF]

BibTeX Entry

@article{nime2025_84,
 abstract = {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.},
 address = {Canberra, Australia},
 articleno = {84},
 author = {Lancelot Blanchard and Cameron Holt and Joseph Paradiso},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 doi = {10.5281/zenodo.15698966},
 editor = {Doga Cavdir and Florent Berthaut},
 issn = {2220-4806},
 month = {June},
 numpages = {4},
 pages = {578--581},
 title = {AI Harmonizer: Expanding Vocal Expression with a Generative Neurosymbolic Music AI System},
 track = {Paper},
 url = {http://nime.org/proceedings/2025/nime2025_84.pdf},
 year = {2025}
}