Dataset Card for MusicCaps

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://kaggle.com/datasets/googleai/musiccaps
• Repository:
• Paper:
• Leaderboard:
• Point of Contact:

Dataset Summary

The MusicCaps dataset contains 5,521 music examples, each of which is labeled with an English aspect list and a free text caption written by musicians. An aspect list is for example "pop, tinny wide hi hats, mellow piano melody, high pitched female vocal melody, sustained pulsating synth lead", while the caption consists of multiple sentences about the music, e.g.,

"A low sounding male voice is rapping over a fast paced drums playing a reggaeton beat along with a bass. Something like a guitar is playing the melody along. This recording is of poor audio-quality. In the background a laughter can be noticed. This song may be playing in a bar."

The text is solely focused on describing how the music sounds, not the metadata like the artist name.

The labeled examples are 10s music clips from the AudioSet dataset (2,858 from the eval and 2,663 from the train split).

Please cite the corresponding paper, when using this dataset: http://arxiv.org/abs/2301.11325 (DOI: 10.48550/arXiv.2301.11325)

Dataset Usage

The published dataset takes the form of a .csv file that contains the ID of YouTube videos and their start/end stamps. In order to use this dataset, one must download the corresponding YouTube videos and chunk them according to the start/end times.

The following repository has an example script and notebook to load the clips. The notebook also includes a Gradio demo that helps explore some samples: https://github.com/nateraw/download-musiccaps-dataset

Supported Tasks and Leaderboards

[More Information Needed]

Languages

[More Information Needed]

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

ytid

YT ID pointing to the YouTube video in which the labeled music segment appears. You can listen to the segment by opening https://youtu.be/watch?v={ytid}&start={start_s}

start_s

Position in the YouTube video at which the music starts.

end_s

Position in the YouTube video at which the music end. All clips are 10s long.

audioset_positive_labels

Labels for this segment from the AudioSet (https://research.google.com/audioset/) dataset.

aspect_list

A list of aspects describing the music.

caption

A multi-sentence free text caption describing the music.

author_id

An integer for grouping samples by who wrote them.

is_balanced_subset

If this value is true, the row is a part of the 1k subset which is genre-balanced.

is_audioset_eval

If this value is true, the clip is from the AudioSet eval split. Otherwise it is from the AudioSet train split.

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

This dataset was shared by @googleai

Licensing Information

The license for this dataset is cc-by-sa-4.0

Citation Information

[More Information Needed]

Contributions

[More Information Needed]