That's certainly useful, and what Echoprint and MusicBrainz have tried to do.
Unfortunately, many fingerprinting use cases require hashing at different granularities (ie, FFT windows), or need different collision guarantees to trade off space vs. accuracy and so on and so forth.
A perfect example is throwing away part of the SHA-1 hash of a fingerprint. You lose some entropy, but you become more space efficient.
Thus in many cases, while the core algorithm might be the same, the parameters and constraints of the individual use case often mean that the fingerprints themselves aren't universal in size or format.
Unfortunately, many fingerprinting use cases require hashing at different granularities (ie, FFT windows), or need different collision guarantees to trade off space vs. accuracy and so on and so forth.
A perfect example is throwing away part of the SHA-1 hash of a fingerprint. You lose some entropy, but you become more space efficient.
Thus in many cases, while the core algorithm might be the same, the parameters and constraints of the individual use case often mean that the fingerprints themselves aren't universal in size or format.