FolkFriend

As of the end of 2023, FolkFriend has transcribed over 80,000 tunes, and has 800 monthly users in over a dozen countries.

This has been a very long running and sophisticated project to implement a “Shazam” like service for traditional Scottish and Irish music. A service that does this already exists, called “Tunepal”, which was completed as a PhD project around 2010. However, FolkFriend provides a service that works offline, is much faster and much more accurate, works on a greater range of devices (it can even run on a smartwatch), and is completely free. You can see feedback from users on thesession.org. This is due to a more sophisticated algorithm, utilizing advances in signal processing and mobile processing power to transcribe live music in noisy environments (e.g., traditional pub sessions) and search against a database of 40,000 tunes.

This is performed in the browser on the client device, such as a mobile, runs entirely without an internet connection (after the first load), and can process queries in around 200-1000 milliseconds. This involves recording the audio samples, performing frequency domain analysis and filtering, using dynamic programming and probabilistic techniques to devise the sequence of notes, and querying the database using an alignment algorithm - all running on the user’s mobile in under a second.

You can read more about this open-source project on the Github page. You can access this service for free at folkfriend.app. I am intending to write a series of further blog posts detailing each of the key steps of FolkFriend, partly to share with people some of the main problems I’ve spent years solving, but also to provide a means of coherently documenting actually how the algorithm works, in a more accessible format than comments spread throughout source code.

Watch this space for updates soon!