Values below 0.33 most likely represent an instrumental. Values between 0.33 and 0.66 describe tracks that may contain both music and speech, either in sections or layered, including such cases as rap music. Values above 0.66 describe tracks that are probably made entirely of spoken words.
Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Loudness values are averaged across the entire track and are useful for comparing relative loudness of tracks. Loudness : The overall loudness of a track in decibels (dB).A value above 0.8 provides strong likelihood that the track is live. Higher liveness values represent an increased probability that the track was performed live. Liveness : Detects the presence of an audience in the recording.A value of 0.0 is least danceable and 1.0 is most danceable. Danceability : Measures how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity.1.0 represents high confidence the track is acoustic.
Acousticness : A confidence measure from 0.0 to 1.0 of whether the track is acoustic.These features range from the tempo of a song to its danceability (Yes, you heard right), a measure of how danceable a song is!įor this project, I used 5 Audio features for mood prediction: I wrote a Python script using the Spotipy Library to connect to the Spotify API and get a list of every playlist I’ve ever created and the songs within them.įor each given song, the Spotify API provides its audio features. The first step was to build a dataset of my Spotify songs through Spotify’s handy API! Photo by Fimpli on Unsplash Getting My Spotify Data
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