N (7)

Question 1

What does the E-step in the Baum-Welch algorithm involve?

Answer 1

• Forward likelihoods
• Backward likelihoods
• Transition likelihoods
• Occupation likelihoods

The E-step calculates probabilities based on the current model parameters.

Question 2

What are the components of the M-step in the Baum-Welch algorithm?

Answer 2

• State-transition probabilities
• Output probability densities

The M-step updates the model parameters based on the likelihoods calculated in the E-step.

Question 3

Define state-transition probabilities in the context of the Baum-Welch algorithm.

Answer 3

âij = EtSt(i,j)/ Et Vt(i)

This formula calculates the probabilities of transitioning from one state to another.

Question 4

What is the formula for Gaussian output probabilities in the Baum-Welch algorithm?

Answer 4

Бі = Et v+(i)0+/ Et Yt(i)

This formula estimates the output probabilities for Gaussian distributions.

Question 5

What does the notation I = {A, B} represent in the Baum-Welch algorithm?

Answer 5

I = {A, B} where A = {âij} and B = {bi}

This notation defines the re-estimated model parameters after applying the Baum-Welch algorithm.

Question 6

True or false: The Baum-Welch algorithm requires a single training sequence.

Answer 6

FALSE

The algorithm uses a set of multiple training sequences to update model parameters.