The Million Song Dataset (MSD) contains a variety of metadata and audio features for 1 million songs. The dataset is structured into multiple files, with the main dataset stored in HDF5 format. Here’s a breakdown of the important columns:
1. Metadata
Column Name
Description
Example
song_id
Unique identifier for a song
SOQHXMF12A6D4FD69A
title
Song title
Bohemian Rhapsody
artist_id
Unique identifier for the artist
ARJ7KF01187FB3F5F1
artist_name
Name of the artist
Queen
release
Album or single name
A Night at the Opera
year
Release year
1975
duration
Length of the song in seconds
355.47
track_id
MusicBrainz Track ID
TRMMMYQ128F932D901
2. Audio Features
Column Name
Description
Example
tempo
BPM (beats per minute)
120.5
key
Musical key (0 = C, 1 = C#, …, 11 = B)
5 (F Major)
mode
1 = Major, 0 = Minor
1
time_signature
Time signature (3, 4, or 5)
4 (4/4 time)
loudness
Overall loudness in dB
-5.5
danceability
A measure of how danceable a song is (0-1)
0.8
energy
Energy level of the track (0-1)
0.9
3. Genre & Similarity
Column Name
Description
Example
artist_terms
List of genre tags
['rock', 'classic rock']
artist_familiarity
Popularity score (0-1)
0.85
artist_hotttnesss
Hotness score (0-1)
0.9
similar_artists
List of similar artists’ IDs
['AR1', 'AR2', 'AR3']
4. Additional Features (Segment-Level Analysis)
These are detailed audio features analyzed per second for deeper audio processing:
MFCCs (Mel-Frequency Cepstral Coefficients) – Used in audio signal processing
Pitch & Timbre Features – For sound quality analysis