MFCC

Question 1

What does MFCC stand for?

Answer 1

Mel-Frequency Cepstral Coefficients

Question 2

True or False: MFCCs are used primarily in image processing.

Answer 2

False

Question 3

What is the primary purpose of MFCC in audio processing?

Answer 3

To represent the short-term power spectrum of sound.

Question 4

Fill in the blank: MFCCs are widely used in __________ recognition systems.

Answer 4

speech

Question 5

Which frequency scale does MFCC utilize?

Answer 5

Mel scale

Question 6

What is the first step in calculating MFCC?

Answer 6

Pre-emphasizing the audio signal

Question 7

True or False: MFCCs can be used for speaker identification.

Answer 7

True

Question 8

What does the Mel scale approximate?

Answer 8

The human ear’s perception of sound frequency.

Question 9

What type of analysis is used to derive MFCCs from the audio signal?

Answer 9

Fourier Transform

Question 10

What is the significance of using a cepstral representation in MFCC?

Answer 10

It separates the source and filter characteristics of the signal.

Question 11

How many coefficients are typically used in a standard MFCC calculation?

Answer 11

12 to 13 coefficients

Question 12

What is a common application of MFCC in the field of machine learning?

Answer 12

Feature extraction for audio classification.

Question 13

True or False: MFCCs are invariant to noise in audio signals.

Answer 13

False

Question 14

What is the role of the Discrete Cosine Transform (DCT) in MFCC computation?

Answer 14

To decorrelate the coefficients.

Question 15

Fill in the blank: MFCCs are often used in __________ systems for automatic speech recognition.

Answer 15

ASR (Automatic Speech Recognition)

Question 16

What is the main advantage of MFCC over raw audio signals?

Answer 16

MFCCs provide a compact representation of audio features.

Question 17

Which process is performed after taking the logarithm of the power spectrum in MFCC computation?

Answer 17

Applying the Discrete Cosine Transform (DCT)

Question 18

True or False: MFCCs can capture information about the timbre of sounds.

Answer 18

True

Question 19

What is the typical frame size used when calculating MFCCs?

Answer 19

20 to 40 milliseconds

Question 20

What is the purpose of windowing in the MFCC process?

Answer 20

To minimize spectral leakage.

Question 21

What type of audio features does MFCC focus on?

Answer 21

Spectral features

Question 22

Fill in the blank: MFCCs are less sensitive to __________ compared to other features.

Answer 22

noise

Question 23

What is the main disadvantage of MFCCs when used in noisy environments?

Answer 23

They may lose important details of the audio signal.

Question 24

True or False: MFCCs can be used in music genre classification.

Answer 24

True

Question 25

What type of signal processing technique is MFCC considered?

Answer 25

Feature extraction technique

Question 26

What does a higher number of MFCC coefficients indicate?

Answer 26

More detailed representation of the audio signal.