8 Music & Lyrics
Artists create and perform as authors performers music which often has lyrics.
More about ► artists and their performer groups, ensembles, orchestras, collectives, ► bands.
8.1 Music contents
8.1.1 Voice
is_instrumental: If the recording appears to be instrumental accoring to Essentia.
speachiness: How much speach is heard in the recording according to the Spotify Echo Nest engine.
voice_gender: F for female, M for male, I for instrumental. The voice_gender_probability shows how certain the Essentia engine was about the gender of the singer.
The voice_gender property is different from the artist_gender property. The voice_gender is applicable for bands, ensembles because it tries to guess the performer’s gender and not that of the composer.
8.1.2 Mood
mood_acoustics: The probablity and the value of the Essentia perceived accoustiness measurement.
mood_aggressive: The probablity and the value of the Essentia aggressiveness measurement.
mood_electronic:The probablity and the value of the Essentia perceived ‘electronic’ measurement.
mood_happy: The probablity and the value of the Essentia happiness measurement.
mood_sad: The probablity and the value of the Essentia sadness measurement.
mood_relaxed: The probablity and the value of the Essentia relaxed mood measurement.
mood_party: The probablity and the value of the Essentia party mood measurement.
timbre: The probablity and the value of the Essentia ‘timbre’ value, which has a robust connection with the impression of “brightness” of a sound.
8.1.3 Genre
Genres are taxonomies to organize music. When no consistent method is used to attach a genre label to a music, we talk about folksonomies. Genres has a consistent set of criteria.
The Essentia measures as based on how close the song is to the sound of reference genre datasets. While they do not map the song to a precise taxonomy, their values are very useful to find similar songs to a recording, because they attach a value to 8 dimensions of a recording, such as how much it is similar to blues songs, alternative songs, etc.
genre_dortmund: The percieved genre by Essentia on the basis of the TU Dortmund Music Audio Benchmark Data Set, values alternative, blues, electronic, folkcountry, funksoulrnb, jazz, raphiphop, rock.
genre_dortmund_blues: how much the song resembles the reference blues songs in the TU Dortmund Music Audio Benchmark Data Set.
The Spotify genres follow the taxonomy of the Spotify recommender sytem. A song may have zero, one, two or more genres attached to it, which will be used to find similar songs or suitable audiences for a song on the Spotify platform.
The Bandcamp folksonomies are self-attached genre tags by the artists or their labels. They do not follow a consistent taxonomy.
8.1.4 Rhythm
bpm: Beats per minute.
beats_count: Total beats counted by Essentia in the recording.
beat_onset: The onset beat of the recording according to Essentia.
8.1.5 Danceability
danceability_spotify: The level of danceability according to the Spotify’s Echo Nest engine.
danceability_essentia: The level of danceability according to the Essentia model.
8.1.6 Tonality
is_atonal: If the song is atonal (1) or tonal (0).
key_essentia: The key of the song according to the Essentia engine.
key_spotify: The key of the song according to the Spotify Echo Nest engine.
tuning_frequency: The apparant tuning frequency for the normal A sound on the recording.
chords_changes_rate