[drc500free]

Having spent a decade in biometrics technology consulting, which is a similar "identify whether this thing is unique, and also you might use this in court" set of technologies... I wonder what the error rates are here.

Oddly enough, court testimony for e.g. fingerprint analysis hangs on the testimony of a human expert claiming 100% certainty, rather than the error characteristics of an automated algorithm. But we DO have recorded and proven False Match and False Non-Match rates from the manufacturers, independent companies, and NIST when it comes to algorithmic techniques. This seems similar to voice comparisons, where error rates are a function of how long the sample is.

I can see fairly easily showing that there are no clear discontinuities in the hum compared to what would be expected from random splicing (though as a defense attorney I would challenge that the very people who are presenting the clip are the ones introducing a spoofable signal; biometric error rates are against RANDOM and non-adversarial presentation, spoofing detection is an entirely different beast).

However, showing uniqueness of a hum sample that is n seconds long compared to the entire continuous history of background hum would be a more rigorous analysis. I wonder if the defense team requested that given that this was a new and unproven technique.