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Purchase Pop Dataset
"Pop" is an exciting AI music dataset meticulously curated to showcase the pop genre's catchy melodies, vibrant rhythms, and contemporary sounds. This comprehensive collection features pop tracks from various eras and styles, including chart-topping hits and influential classics. With its high-quality recordings and expertly annotated metadata, "Pop" is an invaluable resource for exploring the intricacies of pop music production, songwriting, and performance.
Dataset Specifications
Total Audio Tracks: Up to 100k Pop tracks
Type: Genre (Pop)
File Format: WAV, FLAC, MP3, CSV, JSON
Dataset includes:
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Duration
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Key
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Tempo
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BPM Range
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Mood
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Energy
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Description
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Keywords
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Chord Progressions
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Timestamps
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Time Signature
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Number of Bars
The "Pop" AI music dataset is a comprehensive collection of tracks and samples explicitly curated for advancing the field of music generation in the popular music genre. This diverse dataset encompasses various sub-genres and styles within pop music, including contemporary pop, dance-pop, and indie-pop.
The detailed metadata associated with each sample in the "Pop" dataset provides valuable insights into the musical elements, including information about the tempo, key, instrumentation, vocal styles, chord progressions, and song structure. This dataset is invaluable for pushing the boundaries of music generation and fostering innovation in pop music.
This contextual information allows researchers and AI algorithms to delve into the intricate dynamics of pop music and develop sophisticated models capable of generating compelling and authentic pop compositions.
