Dataset guide · 机器学习与语料

Kukedlc/suno-ai-music-dataset

A multi-genre curated AI music dataset generated with Suno V5.5 (chirp-fenix), covering 100+ sub-sub-genres, including MP3 audio, cover art, generation prompts, and 32-column metadata.

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机器学习与语料Free to access

Key facts

InstitutionKukito
Coverage100+ sub-sub-genres across electronic, hip-hop, Latin, jazz, world, rock, ambient, pop, reggae, classical
Time spanMay 2026
ScaleApproximately 200-300 tracks (growing), total file size 4.02 GB, 1714 files
LicenseCreative Commons Attribution 4.0 International (CC-BY-4.0)
AccessHugging Face

Contents & fields

The dataset contains MP3 audio files, JPG cover art, and a master CSV file (biblioteca_master.csv) with 32 columns of metadata. All metadata is keyed by Suno's UUID. Fields include:

  • id——Suno-issued UUID, primary key
  • title——Track title
  • hoja_id_pipeline——Internal pipeline identifier
  • major_model_version——Suno model family (e.g., v5.5)
  • model_name——Specific model variant (e.g., chirp-fenix)
  • status——Suno processing status
  • duration——Track duration in seconds
  • is_instrumental——Boolean for instrumental tracks
  • tags——Free-form tag string at generation
  • tax_radio_destino——Target radio/listener context label
  • tax_suno_capability——Suno capability classification
  • prompt——Exact text prompt used for generation

Research uses

This dataset is suitable for fine-grained audio classification, text-to-music conditioning experiments, music recommendation and similarity research, benchmarks for music tagging and auto-DJ systems, studies of AI music generator capabilities and failure modes, and training material for derivative music-generation models (subject to license terms).

This card was drafted from the source page; institution, coverage, time span, scale, fields and license are subject to the official page (pending human review).

Keywords

SunoAI musicmulti-genreaudio datasettext-to-musicCC-BY-4.0

Access & license

License: License pending verification | Free to access

Why this is hard to get on your own

Obtain a high-quality, multi-genre AI-generated music dataset with detailed metadata for audio classification or text-to-music research.

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