Minimal Feature Analysis for Isolated Digit Recognition for varying encoding rates in noisy environments. (arXiv:2208.13100v1 [cs.CL])

This research work is about recent development made in speech recognition. In
this research work, analysis of isolated digit recognition in the presence of
different bit rates and at different noise levels has been performed. This
research work has been carried using audacity and HTK toolkit. Hidden Markov
Model (HMM) is the recognition model which was used to perform this experiment.
The feature extraction techniques used are Mel Frequency Cepstrum coefficient
(MFCC), Linear Predictive Coding (LPC), perceptual linear predictive (PLP), …

analysis arxiv encoding feature