Objective metrics for audio quality estimation is a tool commonly used to develop audio products, from mobile phones to headphones, hearing aids and audio codec

Objective metrics for audio quality estimation is a tool commonly used to develop audio products, from mobile phones to headphones, hearing aids and audio codecs. I worked briefly in that area some years ago, and have put some notes together at: https://github.com/jonnor/machinehearing/blob/master/audio-quality/README.md https://github.com/jonnor/machinehearing/blob/master/audio-q... In your usecases you would want a metric that only needs the single audio clip, without an original/pristine reference. This is called a "reference-free" / "non-intrusive" / "single-ended" metric. Detecting re-encoding or double encoding is sometimes researched, though mostly for audio forensic purposes. Conceptually it would be possible to use the encoding with different codecs and nitrates/settings on a sizable corpus of music, to learn a ML model that can learn to identify the "true" bitrate on new unseen audio clips.