Feature Vector from an audio signal I want to develop a feature vector from an audio input.

Up to now, I have identified fundamental frequency, max phonation time, timbre to be among the key features to be identified.

Can someone please confirm whether it will be possible to extract these features from the audio?
Have a good read of various features that can be extracted from popular audio analysis libraries like librosa: https://librosa.github.io/librosa/feature.html


Fundamental frequency (F0) can definitely be extracted. This itself a whole subfield, so google and previous SO questions are your best starting point after reading through what a pitch tracker looks like.
For max phonation time, MFCCs are typically the features computed in the front-end of a speech recognition system, which can give you "phone" sequences and their timing. But this would be a lot of processing as the concept of a "phone" in a speaker-independent sense is quite far from raw audio features one might compute directly on the audio signal (like RMS, ZCR, spectral features, etc)
For timbre, have a read through Bello's notes: http://www.nyu.edu/classes/bello/MIR_files/timbre.pdf


Good luck!