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Introduction:
Are you tired of spending hours manually labeling music datasets for your AI models?
Introducing MusicLM by Google, the ultimate solution for music labeling tasks. With MusicCaps, a comprehensive dataset of 5,521 music clips, you can now effortlessly train your models to recognize aspects and moods in music.
Featuring a rich aspect list and free-text captions written by musicians, MusicCaps provides detailed descriptions of how the music sounds, including instruments and mood. Sourced from the AudioSet dataset, MusicCaps is licensed under Creative Commons BY-SA 4.0 and is conveniently divided into eval and train splits.
Each clip in MusicCaps is labeled with metadata, such as YT ID, start and end positions in the corresponding YouTube video, AudioSet labels, aspect list, caption, author ID, balanced subset indication, and AudioSet eval split. This comprehensive dataset is specifically designed for music description tasks, making it an invaluable resource for AI developers and researchers.
Save time and enhance the accuracy of your music analysis models with MusicLM by Google. Unlock the potential of AI in music labeling today.
Overview:
MusicLM by Google is an AI tool that utilizes the MusicCaps dataset. This dataset consists of 5,521 music clips, each lasting 10 seconds, and is accompanied by both an aspect list and a free-text caption written by musicians. The aspect list comprises adjectives that describe various aspects of the music, such as its genre, sound characteristics, and instrumental elements. The free-text caption provides a detailed description of the music, including information about the instruments used and the overall mood. The MusicCaps dataset is derived from the AudioSet dataset and is divided into an evaluation and training split. It is licensed under the Creative Commons BY-SA 4.0 license. Each music clip in the dataset is labeled with metadata, including the YouTube ID of the video in which the music segment appears, the start and end positions of the clip in the video, labels from the AudioSet dataset, the aspect list, the caption, the author ID (for sample grouping), information about whether it is a balanced subset, and its AudioSet evaluation split. This dataset is specifically designed for music description tasks.
Benefits:
- Large dataset: MusicLM by Google provides a dataset of 5,521 music clips, each lasting 10 seconds.
- Aspect list: The dataset includes an aspect list, which consists of adjectives describing how the music sounds, such as “pop,” “tinny wide hi hats,” “mellow piano melody,” “high pitched female vocal melody,” and “sustained pulsating synth lead.”
- Free-text caption: Each music clip is labeled with a free-text caption that provides a detailed description of how the music sounds, including information about instruments and mood.
- Metadata: The dataset includes metadata for each clip, such as the YouTube ID of the video in which the music segment appears, start and end positions in the video, labels from the AudioSet dataset, author ID, and information about whether it is a balanced subset or part of the AudioSet eval split.
- Creative Commons license: The MusicCaps dataset is licensed under Creative Commons BY-SA 4.0, allowing users to freely use and share the dataset.
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