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Purchase Lounge Dataset

The lounge dataset is a selected set of audio songs with metadata such as chords, instrumentation, key, tempo, and timestamps. This dataset is ideal for machine learning applications such as generative AI music, MIR, and source separation. It places you in the relaxed atmosphere of lounge music.

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Dataset Specifications

Total Audio Tracks: Up to 100k Lounge tracks
Type: Genre (Lounge)
File Format: WAV, FLAC, MP3, CSV, JSON

Dataset includes:

  • Duration

  • Key

  • Tempo

  • BPM Range

  • Mood

  • Energy

  • Description

  • Keywords

  • Chord Progressions

  • Timestamps

  • Time Signature

  • Number of Bars

Purchasing License

Annual License
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Perpetual License
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Free audio sample available

The lounge dataset is an extensive collection of audio files with finely managed information. This dataset captures the relaxed atmosphere and refined sound of lounge music, a genre that emerged in the mid-twentieth century. Lounge music combines jazz, bossa nova, and easy listening components to produce a distinct sound world. Our dataset provides a full analysis of each recording, including chords, instrumentation, key, tempo, timestamps, and more.

The distinctive combination of instruments used in lounge music, such as piano, saxophone, trumpet, and vibraphone, contributes to its appeal. The genre, which is commonly associated with martini bars and upscale clubs, presents a unique challenge and opportunity for machine learning applications. By training your models on this dataset, you give them the ability to grasp the essence of lounge music, including its intricate melodic structures and seamless integration of various musical parts.

This dataset is more than simply a collection of data points; it's a portal to a world where AI-powered music generation, Music Information Retrieval, and source separation coexist with the refined and timeless elegance of lounge music. Engage your projects in the elegance of lounge music, allowing your models to perfect the craft of generating ambient, fascinating soundscapes that reflect the genre's history and modern evolution.

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