Comment by snet0

I did a similar acoustic side-channel attack as final year project at uni. There's a treasure trove of findings in this area, I'm just waiting for someone to combine methodologies. There are pretty good results using geometric models, trained and untrained statistical models like this and others, and combining these features with assorted language models.

Here's a few random papers I read along the way:

https://doi.org/10.1007/s10207-019-00449-8 - SonarSnoop, which uses a phone's speaker to produce ultrasonic audio that can be used to profile the user's interaction (e.g. entering swipe-based passcodes).

https://people.eecs.berkeley.edu/~daw/papers/ssh-use01.pdf - "Timing Analysis of Keystrokes and Timing Attacks on SSH", a paper from 2001 that uses statistical models of keystroke timings to retrieve passwords from encrypted SSH traffic.

https://doi.org/10.1145/1609956.1609959 - "Keyboard acoustic emanations revisited", which uses hidden Markov models and some other English language features to recover text based on classification via cepstrum features.

https://doi.org/10.1145/2660267.2660296 - "Context-free Attacks Using Keyboard Acoustic Emanations" which uses a geometric approach, using time-difference-of-arrival to estimate physical locations probabilistically.