Engineering Questions with Answers - Multiple Choice Questions

# Artificial Intelligence MCQ – Hidden Markov Model

1 - Question

Which algorithm is used for solving temporal probabilistic reasoning?
a) Hill-climbing search
b) Hidden markov model
c) Depth-first search

Explanation: Hidden Markov model is used for solving temporal probabilistic reasoning that was independent of transition and sensor model.

2 - Question

How does the state of the process is described in HMM?
a) Literal
b) Single random variable
c) Single discrete random variable
d) None of the mentioned

Explanation: An HMM is a temporal probabilistic model in which the state of the process is described by a single discrete random variable.

3 - Question

What are the possible values of the variable?
a) Variables
b) Literals
c) Discrete variable
d) Possible states of the world

Explanation: The possible values of the variables are the possible states of the world.

4 - Question

a) Temporal model
b) Reality model
c) Probability model
d) All of the mentioned

Explanation: Additional state variables can be added to a temporal model while staying within the HMM framework.

5 - Question

Which allows for a simple and matrix implementation of all the basic algorithm?
a) HMM
b) Restricted structure of HMM
c) Temporary model
d) Reality model

Explanation: Restricted structure of HMM allows for a very simple and elegant matrix implementation of all the basic algorithm.

6 - Question

Where does the Hidden Markov Model is used?
a) Speech recognition
b) Understanding of real world
c) Both Speech recognition & Understanding of real world
d) None of the mentioned

Explanation: None.

7 - Question

Which variable can give the concrete form to the representation of the transition model?
a) Single variable
b) Discrete state variable
c) Random variable
d) Both Single & Discrete state variable

Explanation: With a single, discrete state variable, we can give concrete form to the representation of the transition model.

8 - Question

Which algorithm works by first running the standard forward pass to compute?
a) Smoothing
b) Modified smoothing
c) HMM
d) Depth-first search algorithm

Explanation: The modified smoothing algorithm works by first running the standard forward pass to compute and then running the backward pass.

9 - Question

Which reveals an improvement in online smoothing?
a) Matrix formulation
b) Revelation
c) HMM
d) None of the mention ed

Explanation: Matrix formulation reveals an improvement in online smoothing with a fixed lag.

10 - Question

Which suggests the existence of an efficient recursive algorithm for online smoothing?
a) Matrix
b) Constant space
c) Constant time
d) None of the mentioned