Last.fm Scrobbler for YouTube™

This extension seemingly scrobble watched YouTube videos to the "Last.fm" service without visiting the site. Automatic scrobbling takes place 30 seconds after the music is played or at the end of the track if the track is less than 30 seconds. You can also manually scrobble the currently played song by pressing the count-down label.

Using this extension you can also like or dislike YouTube songs without the need to open the actual "Last.fm" website.

Note that to prevent unwanted scrobbling, the extension pauses the count down when the song is paused. Also, the scrobbling label, as well as the like button, only appears if you are watching a track in the "Music" or "Entertainment" categories. Of course, the user can extend categories to include localized names or completely remove the category check.

Usage Instruction:
1. Install the extension
2. Open a YouTube music or refresh an existing music tab
3. Wait for the extension to show "Connect to Last.fm"

Features:
1. Supports Love/unlove tracks
2. Supports automatic artist name detection
3. Supports cleaning the track extra info
4. Supports manually modifying the track name or artist name (if the song doesn't get recognized)
5. Supports reporting the currently playing track to "Last.fm"
6. Supports YouTube Music interface

Why do I need this extension?
If you enjoy watching music videos, this extension helps you to discover new music tracks. The "Last.fm" service suggests new music tracks based on your listening habits.

What is the "Last.fm" service? [from Wikipedia]
Last.fm is a music website founded in the United Kingdom in 2002. Using a music recommender system called "Audioscrobbler", Last.fm builds a detailed profile of each user's musical taste by recording details of the tracks the user listens to, either from Internet radio stations, or the user's computer or many portable music devices. This information is transferred ("scrobbled") to Last.fm's database either via the music player (including, among others, Spotify, Deezer, Tidal, MusicBee, SoundCloud, and Anghami) or via a plug-in installed into the user's music player. The data is then displayed on the user's profile page and compiled to create reference pages for individual artists.