An adaption of Markov state machines where the machine and transitions are managed by example and not directly known. Using some algorithms the machine can be trained to immitate a set of state transitions to produce given example pairs, or consulted given an output to see what the most likely transitions to produce it were.

• Markov models

Dragon Speak

These were also the secret to Dragon Naturally Speaking according to "How to Create a Mind."

• Sound is first run through band passes to find energy at a given set of frequencies (immitating the cochlea)
• These sound signatures are kept in a vector quantizing codebook to replace sound fragments with ex. 4,000 exemplars.
• Hidden Markov Models are used so that sound can be paired with a list of exemplars and the desired transcription information.
• Sound coming in is first filtered, matched to the nearest codebook, then the HMM is used to map the codebook sequence back to phonemes etc.