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Soundtrack dataset for AI-Generated Music

This dataset goes above and beyond, including not only the expected chords, instrumentation, key, and tempo, but also precise timestamps and other details. With this treasure trove, you can unleash the power of your machine-learning models. It's specifically built for generative AI music, Music Information Retrieval (MIR), source separation, and a variety of other advanced applications.

Take a tour through the varied applications of training models on soundtrack music. Soundtracks are a fascinating area in which emotion and narrative blend perfectly with musical production. Training your machine learning model on this dataset brings up new options for creating emotive, cinematic music. Explore the deep nuances of chord progressions, instrumentation choices, and the dynamic interplay of key and tempo that characterize the compelling soundscapes of soundtracks.

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Dataset Highlights


High-Quality Recordings

All audio files in the dataset are meticulously recorded and curated, ensuring top-notch audio quality and fidelity to elevate the overall production value of any soundtrack or audio project.

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Metadata and Tagging

The dataset includes comprehensive metadata and tagging for easy search and navigation, enabling users to quickly find the perfect sound elements to complement their scenes or enhance their storytelling.


Multifaceted Audio Elements

The "Soundtrack" dataset includes a diverse array of audio elements, such as sound effects, dialogue samples, ambient recordings, and film scores, providing a comprehensive resource for sound designers, filmmakers, and multimedia creators.


Versatility Across Media

Designed to enhance various forms of audiovisual storytelling, the dataset caters to the needs of filmmakers, game developers, and content creators, offering a versatile palette for crafting immersive and engaging soundscapes.


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