Our motto is “We hear everything everywhere and tell everyone who wants to know.” Something we don’t mention so often but we feel equally proud of is how we do it: audio fingerprinting.
An audio fingerprint is a condensed digital summary of an audio signal, generated by extracting acoustic relevant characteristics of a piece of audio content. Along with matching algorithms, this digital signature permits to identify different versions of a single recording with the same title.
Fragment of the spectrogram of all BMATers saying Music Innovators. A spectrogram is the basis for our audio fingerprinting.
When a song is ingested in our database, we automatically generate and store its fingerprint which we’ll later use to identify the audios we record across TVs, radios and venues. Just like with human fingerprints we can compare a recording fingerprint against a global database of songs and locate its match within seconds.
But as every recording is unique, identifying an audio (matching it with its fingerprint and metadata) requires it to be almost identical to the stored and fingerprinted song. Not strictly identical because a good fingerprinting technology must be robust against certain sound degradations and needs to detect when the song isn’t itself anymore.
We believe human perception determines this boundary and we train our technology to develop the same sensitivity so that when we humans cannot recognise a song, our matching algorithm doesn’t identify it either.