{"id":4766,"date":"2022-12-17T22:17:02","date_gmt":"2022-12-17T22:17:02","guid":{"rendered":"https:\/\/dalelane.co.uk\/blog\/?p=4766"},"modified":"2024-01-29T20:27:37","modified_gmt":"2024-01-29T20:27:37","slug":"spotify-extension-for-scratch","status":"publish","type":"post","link":"https:\/\/dalelane.co.uk\/blog\/?p=4766","title":{"rendered":"Spotify extension for Scratch"},"content":{"rendered":"

In this post, I want to share a new Scratch extension that I made this week, explain what it does<\/a>, and suggest a few ideas<\/a> for the sorts of ways that it could be used.<\/strong><\/p>\n

<\/p>\n

Overview<\/h3>\n

The extension makes some of the data from the Spotify Audio Features API<\/a> available as blocks in Scratch.<\/p>\n

It means you can get numeric values representing different characteristics of songs, directly into a Scratch project.<\/p>\n


\n<\/a><\/p>\n

The blocks<\/h3>\n

Adapted from the Spotify API docs<\/a>.<\/em><\/p>\n

search for<\/code><\/p>\n

This searches Spotify’s library for a track. You can put artist and title in any order, and it’s fairly tolerant of spelling mistakes.<\/p>\n

play preview<\/code><\/p>\n

This plays a 30-second preview of the last track that you searched for. The block will stay active until the song preview has completed, so any blocks attached to the bottom of this block will be run after the preview has finished playing.<\/p>\n

acousticness score<\/code><\/p>\n

This returns a confidence score of whether the track is acoustic. The score is between 0.0 and 1.0, with 1.0 representing high confidence the track is acoustic.<\/p>\n

danceability<\/code><\/p>\n

This describes how suitable a track is for dancing – using a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. The score is between 0.0 and 1.0, with 0.0 being least danceable and 1.0 most danceable.<\/p>\n

duration<\/code><\/p>\n

The length of the full track (not the preview clip) in seconds.<\/p>\n

energy<\/code><\/p>\n

This returns a perceptual measure of intensity and activity, between 0.0 and 1.0.<\/p>\n

Typically, energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale. Perceptual features contributing to this attribute include dynamic range, perceived loudness, timbre, onset rate, and general entropy.<\/p><\/blockquote>\n

instrumentalness<\/code><\/p>\n

This describes whether the track has any vocals. The score is between 0.0 and 1.0.<\/p>\n

“Ooh” and “aah” sounds are treated as instrumental in this context. Rap or spoken word tracks are clearly “vocal”. The closer the instrumentalness value is to 1.0, the greater likelihood the track contains no vocal content. Values above 0.5 are intended to represent instrumental tracks, but confidence is higher as the value approaches 1.0.<\/p><\/blockquote>\n

key (code)<\/code><\/p>\n

This returns a number representing the key the track is in, using pitch class notation<\/a>. If no key was detected, the value is -1.<\/p>\n

key (name)<\/code><\/p>\n

This returns a string with the name of the key that the track is in. Names are described using sharps rather than flats (e.g. B? will be returned as A#)<\/p>\n

liveness<\/code><\/p>\n

This returns a prediction of whether the track was performed live. This is done by detecting the presence of an audience in the recording. The value is between 0.0 and 1.0, with higher values representing a higher probability that the track was live.<\/p>\n

loudness<\/code><\/p>\n

This returns the overall loudness of the track in decibels.<\/p>\n

Loudness values are averaged across the entire track and are useful for comparing relative loudness of tracks. Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Values typically range between -60 and 0 db.<\/p><\/blockquote>\n

mode<\/code><\/p>\n

This returns the modality (major or minor) of the track. Major is represented by 1, minor is represented by 0.<\/p>\n

speechiness<\/code><\/p>\n

This detects the presence of spoken words in a track.<\/p>\n

The more exclusively speech-like the recording (e.g. talk show, audio book, poetry), the closer to 1.0 the attribute value. Values above 0.66 describe tracks that are probably made entirely of spoken words. 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 below 0.33 most likely represent music and other non-speech-like tracks.<\/p><\/blockquote>\n

beats per minute<\/code><\/p>\n

This returns an estimate for the tempo of the track.<\/p>\n

beats per bar<\/code><\/p>\n

This returns an estimate for the time signature of the track.<\/p>\n

happiness<\/code><\/p>\n

This returns a number describing the musical positiveness conveyed by a track. The score is between 0.0 and 1.0, with higher scores representing more positive tracks (e.g. happy, cheerful, euphoric), and lower scores representing negative tracks (e.g. sad, depressed, angry).
\n<\/a><\/p>\n

Project ideas<\/h3>\n

The reason for creating the extension was to try creating some machine learning projects, training a machine learning model using some or all of this data. I’ve not tried doing that yet, so in the meantime, here are a few quick ideas for the sorts of things that can simply be made using the extension.<\/p>\n

Sprites that dance in time to music<\/h4>\n

You can animate a sprite by switching costumes. Using the beats per minute<\/code> block, you can animate a sprite in time to music, so it looks like they’re dancing.<\/p>\n

You can include the danceability<\/code> block as well to make your sprite refuse to dance to songs that aren’t danceable enough!<\/p>\n