Applying dtw on mfcc

1. Is MFCC a feature extraction?
2. Why is MFCC used for feature extraction?
3. What is DCT in MFCC?

Is MFCC a feature extraction?

The MFCC feature extraction technique basically includes windowing the signal, applying the DFT, taking the log of the magnitude, and then warping the frequencies on a Mel scale, followed by applying the inverse DCT. The detailed description of various steps involved in the MFCC feature extraction is explained below.

Why is MFCC used for feature extraction?

It is observed that extracting features from the audio signal and using it as input to the base model will produce much better performance than directly considering raw audio signal as input. MFCC is the widely used technique for extracting the features from the audio signal.

What is DCT in MFCC?

DCT is the last step of the main process of MFCC feature extraction. The basic concept of DCT is correlating value of mel spectrum so as to produce a good representation of property spectral local. Basically the concept of DCT is the same as inverse fourier transform.