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Acquisition for research is separate from unresolved redistribution rights; no public rehosting in this task.", "citation": "Tzanetakis and Cook (2002), Musical Genre Classification of Audio Signals; Sturm (2013), The GTZAN dataset: Its contents, its faults, their effects on evaluation, and its future use; Kereliuk, Sturm and Larsen (2015), Deep learning and music adversaries; Sturm (2014), The state of the art ten years after a state of the art.", "license": "Recording copyright/license unspecified in maintainer card; public research acquisition only. Apache/GPL/MIT software labels do not license recordings.", "metadata_url": "https://huggingface.co/datasets/marsyas/gtzan", "notes": "Maintainer namespace is public,ungated and anonymously downloadable; original raw TAR.GZ has LFS SHA256, not a resampled Parquet representation. Bounded sampleWAV header verifies22050Hz monoPCM16. Source-wide decoding remains a preparation check. Public distribution is an acquisition endpoint, not proof of rights to publish a new mirror. No new rehosting is authorized or performed.", "quality_exclusions": "Demonstrably wronggenre labels and genuinely unreadable requiredintervals are task masks. Retain noisy/difficult clips, duplicates and cross-dataset overlap in source acquisition. Historicalfaultfiltered protocol supplied as an optionalreference, not applied as a blanketqualityfilter.", "release": "Native maintainer archive d2146561ecc7df707d9e6b8318885fe6a39668a2; Sturm reference partitions fedc781026cf1a20034830f8071c98d93a422016", "scope": "optional_legacy_diagnostic", "selection": "Acquire all1000original native WAV clips and fault/artist metadata. 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Confirmed wronggenre targets require correction/masking before any newvalidityclaim.", "official_split": "Original release has no universal officialsplit. 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