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Synthpop dataset for AI-Generated Music

This dataset is intended for machine learning training applications, and allows for a wide range of use cases. Train your generative AI music model to create unique Synthpop-inspired tracks that reflect the essence of the genre. Explore Music Information Retrieval (MIR) as you analyze and extract patterns, resulting in a better knowledge of Synthpop's distinct musical characteristics.

Examine source separation difficulties using the rich information, which allows your model to recognize and separate distinct pieces within a track. Discover what lies behind the synthesis processes, revealing the numerous layers that make Synthpop a unique and dynamic genre in the world of electronic music.

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Dataset Highlights


Rhythmic Diversity

Explore a wide range of rhythmic patterns crafted by AI, reflecting the infectious beats and grooves that define synthpop. From upbeat and energetic rhythms to more laid-back and contemplative tempos, Synthpop offers a diverse selection for musical exploration.

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Genre Fusion

Synthpop is not confined to a singular style; it embraces the spirit of experimentation. The dataset seamlessly blends elements from various musical genres, pushing the boundaries of what synthpop can encompass. Expect to encounter influences from electronic, pop, and even experimental music.



Dive into a rich palette of synthetic sounds and electronic instruments that define the distinctive character of synthpop. Synthpop's AI-generated instrumentation captures the essence of classic synthesizers while introducing novel sonic elements, resulting in a contemporary and forward-looking musical experience.


Versatility for Creativity

Whether you're a music producer, researcher, or enthusiast, Synthpop provides a versatile playground for creative endeavors. Use the dataset to inspire new compositions, experiment with AI-generated elements, or analyze the evolving landscape of AI-generated music within the synthpop genre.


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