Description : Which specifies the prior probability of each utterance? a) Sound model b) Model c) Language model
Last Answer : c) Language model
Description : Where does the additional variables are added in HMM? a) Temporal model b) Reality model c) Probability model d) All of the mentioned
Last Answer : a) Temporal model
Description : 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
Last Answer : a) Speech recognition
Description : Parts-of-Speech tagging determines ___________ a) part-of-speech for each word dynamically as per meaning of the sentence b) part-of-speech for each word dynamically as per sentence structure c) all part-of-speech for a specific word given as input d) all of the mentioned
Last Answer : d) all of the mentioned
Description : When talking to a speech recognition program, the program divides each second of your speech into 100 separate __________ a) Codes b) Phonemes c) Samples d) Words
Last Answer : c) Samples
Description : For speech understanding systems to gain widespread acceptance in office automation, they must feature ____________ a) speaker independence b) speaker dependence c) isolated word recognition d) all of the mentioned
Last Answer : a) speaker independence
Description : Which approach to speech recognition avoids the problem caused by the differences in the way words are pronounced according to context? a) continuous speech recognition b) connected word recognition c) isolated word recognition d) speaker-dependent recognition
Last Answer : c) isolated word recognition
Description : ______________ is/are the way/s to represent uncertainty. a) Fuzzy Logic b) Probability c) Entropy d) All of the mentioned
Last Answer : d) All of the mentioned
Description : How the entries in the full joint probability distribution can be calculated? a) Using variables b) Using information c) Both Using variables & information d) None of the mentioned
Last Answer : b) Using information
Description : What is meant by probability density function? a) Probability distributions b) Continuous variable c) Discrete variable d) Probability distributions for Continuous variables
Last Answer : d) Probability distributions for Continuous variables
Description : Where does the dependance of experience is reflected in prior probability sentences? a) Syntactic distinction b) Semantic distinction c) Both Syntactic & Semantic distinction d) None of the mentioned
Last Answer : a) Syntactic distinction
Description : What is used for probability theory sentences? a) Conditional logic b) Logic c) Extension of propositional logic
Last Answer : c) Extension of propositional logic
Description : Which is true for Decision theory? a) Decision Theory = Probability theory + utility theory b) Decision Theory = Inference theory + utility theory c) Decision Theory = Uncertainty + utility theory d) Decision Theory = Probability theory + preference
Last Answer : c) Decision Theory = Uncertainty + utility theory
Description : Stochastic hill climbing chooses at random from among the uphill moves; the probability of selection can vary with the steepness of the uphil1 move. a) True b) False
Last Answer : a) True
Description : In Bayes theorem, what is meant by P(Hi|E)? a) The probability that hypotheses Hi is true given evidence E b) The probability that hypotheses Hi is false given evidence E c) The probability ... Hi is true given false evidence E d) The probability that hypotheses Hi is false given false evidence E
Last Answer : a) The probability that hypotheses Hi is true given evidence E
Description : Subject orientation A . The science of collecting, organizing, and applying numerical facts B. Measure of the probability that a certain hypothesis is incorrect given certain observations. C. ... specially built around all the existing applications of the operational data D . None of these
Last Answer : C. One of the defining aspects of a data warehouse, which is specially built around all the existing applications of the operational data
Description : Which of the following is used for probability theory sentences? a) Conditional logic b) Logic c) Extension of propositional logic d) None of the mentioned
Description : Define joint probability distribution
Last Answer : This completely specifies an agent's probability assignments to all propositions in the domain.The joint probability distribution p(x1,x2,--------xn) assigns probabilities to all possible atomic events;where X1,X2------Xn 10 =variables.
Description : Define probability distribution
Last Answer : Eg. P(weather) = (0.7,0.2,0.08,0.02). This type of notations simplifies many equations.
Description : Define conditional probability?
Last Answer : Once the agents has obtained some evidence concerning the previously unknown propositions making up the domain conditional or posterior probabilities with the notation p(A/B) is used. This is important that p(A/B) can only be used when all be is known.
Description : Speech Segmentation is a subtask of Speech Recognition. a) True b) False
Description : Given a sound clip of a person or people speaking, determine the textual representation of the speech. a) Text-to-speech b) Speech-to-text c) All of the mentioned d) None of the mentioned
Last Answer : b) Speech-to-text
Description : What is viewed as problem of probabilistic inference? a) Speech recognition b) Speaking c) Hearing d) Utterance
Description : What kind of signal is used in speech recognition? a) Electromagnetic signal b) Electric signal c) Acoustic signal d) Radar
Last Answer : c) Acoustic signal
Description : What is the dominant modality for communication between humans? a) Hear b) Speech c) Smell d) None of the mentioned
Last Answer : b) Speech
Description : What kind of perception is used in printing? a) Optical character recognition b) Speech recognition c) Perception d) None of the mentioned
Last Answer : a) Optical character recognition
Description : What is the complex system of structured message? a) Languages b) Words c) Signs d) Speech
Last Answer : a) Languages
Description : What is the intentional exchange of information brought about by production and perception? a) Hearing b) Communication c) Speech d) None of the mentioned
Last Answer : b) Communication
Description : What will take place as the agent observes its interactions with the world? a) Learning b) Hearing c) Perceiving d) Speech
Last Answer : a) Learning
Description : Which is the only way to learn about the different kinds of human faces? a) Perception b) Speech c) Learning d) Hearing
Last Answer : c) Learning
Description : What enables people to recognize people, animals and inanimate objects reliably? a) Speech b) Vision c) Hear d) Perception
Last Answer : b) Vision
Description : Which of the following contains the output segments of Artificial Intelligence programming? a) Printed language and synthesized speech b) Manipulation of physical object c) Locomotion d) All of the mentioned
Description : Which of the following is not an application of learning? a) Data mining b) WWW c) Speech recognition d) None of the mentioned
Last Answer : d) None of the mentioned
Description : Playing chess, purchasing suggestions on e-commerce site, self-driving cars, speech recognition, and image recognition are the example of ____. A. Narrow AI B. General AI C. Super AI D. None of above
Last Answer : A. Narrow AI
Description : Chomsky’s linguistic computational theory generated a model for syntactic analysis through __________ A. Regular Grammar B. Regular Expression C. Regular Word D. None of these
Last Answer : A. Regular Grammar
Description : ARGEX is an agricultural expert system that gives correct advice to farmers. a) True b) False
Description : The component of an ICAI (Intelligent Computer Assisted Instruction) presenting information to the student is the? a) Student model b) Problem solving expertise c) Tutoring module d) All of the mentioned
Last Answer : c) Tutoring module
Description : The explanation facility of an expert system may be used to ____________ a) construct a diagnostic model b) expedite the debugging process c) explain the system’s reasoning process d) explain the system’s reasoning process & expedite the debugging process
Last Answer : d) explain the system’s reasoning process & expedite the debugging process
Description : Which are partially captured by triphone model? a) Articulation effects b) Coarticulation effects c) Both Articulation & Coarticulation effects d) None of the mentioned
Last Answer : b) Coarticulation effects
Description : Which is used to capture the internal structure of the phones? a) One-state phone model b) Two-state phone model c) Three-state phone mone d) All of the mentioned
Last Answer : c) Three-state phone mone
Description : Which of the following are the advantage/s of Decision Trees? a) Possible Scenarios can be added b) Use a white box model, If given result is provided by a model c) Worst, best and expected values can be determined for different scenarios d) All of the mentioned
Description : A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. a) Decision tree b) Graphs c) Trees d) Neural Networks
Last Answer : a) Decision tree
Description : Which of the following is the component of learning system? a) Goal b) Model c) Learning rules d) All of the mentioned
Description : 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
Last Answer : d) Both Single & Discrete state variable
Description : Which allows for a simple and matrix implementation of all the basic algorithm? a) HMM b) Restricted structure of HMM c) Temporary model
Last Answer : b) Restricted structure of HMM
Description : Which algorithm is used for solving temporal probabilistic reasoning? a) Hill-climbing search b) Hidden markov model c) Depth-first search d) Breadth-first search
Last Answer : b) Hidden markov model
Description : How many terms are required for building a bayes model? a) 1 b) 2 c) 3 d) 4
Last Answer : c) 3