I wouldn't necessarily recommend it, as it is still in development and at a research level at best, but the openmir software that I developed for my Ph.D. is open source (BSD license) and is available on github : https://github.com/openmir/openmir
It is a web based system for doing annotation, audio feature extraction and machine learning on large collections of audio. It can display spectrograms and other representations of audio. It leverages the powerful Marsyas framework audio feature extraction and machine learning ( http://marsyas.info). You can see openmir in action at the new Orchive site: http://orchive.net/recordings/2 I've transitioned out of research myself, but if you have any young students who are good at programming (Python + Javascript) I would love to see someone take this software on. Steven. On Tue, Sep 30, 2014 at 3:03 AM, Jerome Sueur <su...@mnhn.fr> wrote: > I also use Audacity. The labels can be exported in a simple .txt file I > can import in R and then run a batch analysis with seewave. > The only issue is that audacity does not have a utility to label in the > frequency domain. > Best regards, > Jerome >
