2025/09/29 by Nia D'Souza Ganapathy, Ganapathy, Nia D'Souza, Arul Selvamani Shaja +1
Computer Science · Engineering · Social Sciences · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Human Motion and Animation #Multimedia Communication and Technology #Music Technology and Sound Studies #Sound (cs.SD)
paper · pdf · doi:10.48550/arxiv.2509.24463
openalex publication_date 2025/09/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The generation of musically coherent and aesthetically pleasing harmony remains a significant challenge in the field of algorithmic composition. This paper introduces an innovative Agentic AI-enabled Higher Harmony Music Generator, a multi-agent system designed to create harmony in a collaborative and modular fashion. Our framework comprises four specialized agents: a Music-Ingestion Agent for parsing and standardizing input musical scores; a Chord-Knowledge Agent, powered by a Chord-Former (Transformer model), to interpret and provide the constituent notes of complex chord symbols; a Harmony-Generation Agent, which utilizes a Harmony-GPT and a Rhythm-Net (RNN) to compose a melodically and rhythmically complementary harmony line; and an Audio-Production Agent that employs a GAN-based Symbolic-to-Audio Synthesizer to render the final symbolic output into high-fidelity audio. By delegating specific tasks to specialized agents, our system effectively mimics the collaborative process of human musicians. This modular, agent-based approach allows for robust data processing, deep theoretical understanding, creative composition, and realistic audio synthesis, culminating in a system capable of generating sophisticated and contextually appropriate higher-voice harmonies for given melodies.