#Songkong create artist folder for free#

The artist name is an interesting one - the data is coming from which lists the one from the cover as the canonical artist name for the release, but is also linked to which is the canonical name for the artist - we use both as suggestions and that's why you have the two choices you showed in the screenshot. In general, this would be best implemented as a rule I think, because different players will have different demands - I've learnt how primitive some are, and support for multiple artist fields is not an option on some (my own car stereo only supports ID3v1 for example). Analysing existing tags and split those Making sure incoming artist data splits into separate tags Thanks for this feedback artists one is a common request. For people with large collections which need extensive fixing, it could be a great starting point.

However, according to Bliss, this artist name is incorrect and should be 'The Buddy Bregman Orchestra'Īpart from the quality of the database, I liked it a lot and appreciated that it was possible to review suggestions before committing to them. For example, this album cover indicates an artist name of 'Buddy Bregman and his Orchestra': In some cases, the database was just wrong. Or, even worse, tags of the same pairing using a mixture of 'and' and '&' for different albums. a tag which creates a new artist tag of 'Nancy Sinatra & Frank Sinatra' rather than creating two individual artist tags. For example, one of my pet peeves is tags which combine multiple artists into one tag, e.g.

My impression was that I liked the overall concept and design of the app but it was let down by the quality of the data source upon which it relied. I tried it a month ago so unfortunately my memory of it isn't as fresh any more. Provided there were an accurate repository for metadata, which does not exist today, and provided this repository were linked to the digital tracks (ex: AcurrateRip database), then one interesting application would be automatic recognition based on tracks, and not based on albums (as is the case for example with Roon). Those are not things that can be guessed, and they need to be accurate. In terms of 'tagging' (I prefer to talk about metadata), I spend a lot of time adding metadata to my albums - recording dates, venues, and credits. There is also research being done on music analysis to identify the specificty of musicians (ex: what makes a Charlie Parker so identifiable and different from, say, a Johnny Hodges ?).

Here's an example that popped up with a simple Google search - there must be many others: I don't personally find that of any interest, but others may. I think there are already such applications, that can for example identify the 'mood' of tracks, or similar attributes, and are used for automatic suggestions (radio). This service is not really aimed at the individual but surely intelligent tagging like this must be just around the corner for the music enthusiast and personally I can't wait! m4a file types – I have no idea whether this limitation applies to the paid plans).

#Songkong create artist folder for free#

THIS got my attention :) You can test this for yourself for free at (unfortunately the demo only works with. Now for the really interesting part: there are already AI apps which can analyze a music track and identify the genre accurately (90-99% depending on the genre), not by looking up a database but by analyzing the actual music. Other tags such as disk number and total disks are so time consuming to do manually but would be a snap with a smart tagging app. Potential spelling errors could be flagged, as well as track numbers which accidentally found their way into track titles, etc. artist tags which differ slightly but are likely to be the same could be flagged -> 'I found separate tags for 'Beatles' and 'The Beatles'.' Then you could select which tag to apply in all cases or choose to do nothing at all. A program could be written to scan a whole library and look for likely mistakes, e.g. I'm not talking about using an online tagging database because these online libraries contain problems of their own which still have to be corrected but at least they offer a starting point and even tags on commercial platforms such as Spotify or Qobuz are riddled with errors. Having recently spent several days on a tagging project (and I haven't even started with the genre tagging) I was thinking that this job could easily be automated to save a lot of time and to reduce errors.