Hi Mark, thanks for joining the forum. I’ve played around with sound processing with HTM in the past (you can run it against any WAV file):
This demo trains runs an FFT on the audio signal into 10 bins, and I trained 10 NuPIC models, one on each model.
I didn’t really know what I was doing at the time, and I didn’t really find out anything useful. I was trying to see what anomalies it would show, hoping they would partially align with major changes in songs I would play. In the end, it was inconclusive.
If I were to do this again, I would train the models on birdsongs and manually reset each song as they naturally end. You might train 10 models with 10 different songs, then let a bird sing a song. Each model will generate comparable anomaly scores, so you should be able to classify the song this way. However, this is nothing more than current DL techniques also do in other ways.
The cochlea is a complicated organ, and we don’t have an encoder for it yet, however some have tried:
I hope this leads you in the right direction without discouraging you. I believe it is possible, but I don’t know how to do it.