When I am listening to music using head-phones, I find listening to stereo recordings rather tiring, so I am using a cross-feed-plugin (http://bs2b.sourceforge.net) which to my perception improves the spatial perception of the recording a lot (feels to me like having a panoramic perception instead of one that feels like having a pool cue stuck through both of my ears).
Obviously, I don't want to smash binaural recordings by applying cross-feed on top of them. So, this question came to my mind:
Is there any algorithmic way to guess whether a specific recording is binaural or not? Criteria that come to my mind:
- rather easy: lack of cross-correlation -> stereo
- difficult: consistent cross-correlation for certain "components" of the sound (wavelets?) -> binaural
- vague: frequency envelope that is typical for head-transfer-functions -> binaural
Obviously, any such algorithm will have flaws because in fact any binaural recording can be interpreted as a strange stereo signal. And any stereo signal can be interpreted as a binaural recording in a very strange room, where the head is in the middle of a wall and each ear only hears part of the room.
Anyway, is there anything established in that direction?