With neural networks and much faster computers, this is not rocket science today. However, even desktops back in 1999 did not do neural networks as far as I know, let alone a handheld device designed at that time. The recognition on my 6230i works quite well and appears to be live: it starts listening and displays a result about 1 second after you've spoken the matching sample. I can also speak a whole sentence with only the pre-recorded keyword in it, it patiently waits about 4 seconds for me to mention something it recognizes, and shortly after I do it displays the match. (Or if I remain silent, then after 2 seconds it will report no match.)
I've been trying to find how this worked but didn't find anyone talking about it. The results are all about newer devices and how to use the feature, not how it technically worked. Adding keywords like machine learning or "fft" (with quotes) to the search doesn't yield anything either.
Did it have some very basic machine learning? Though that might also need more training data rather than just one recording to match against. Perhaps, then, it used Fast Fourier Transform to extract and then later match the frequencies? The device can play back the recordings (as an aside, it turns out 13-year-old me sounded like a little girl), perhaps because it uses that as a reference and it doesn't merely extract features.
Is it known how these systems (must have) worked?