Natural Language Processing (KAI052) - AKTU Question Paper 2023-24
B.Tech · Semester 5 · Free PDF Download
This is the official AKTU Natural Language Processing Previous Year Question Paper for B.Tech Semester 5, academic session 2023-24. Published by Dr. A.P.J. Abdul Kalam Technical University (AKTU/UPTU), Lucknow. Free PDF download — no login required.
Course:B.Tech
Semester:Semester 5
Session:2023-24
University:AKTU / UPTU
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Questions Asked in 2023-24
Natural Language Processing (KAI052) — complete question paper · 100 marks · 3 Hours
Section AAttempt all q u e s t i o n s i n b r i e f . 2 x 10 = 20
- aHow has NLP evolved over time? 2
- bCan you explain the challenges associated with language modeli ng in NLP?
- cDiscuss strategies for handling ambiguity in parsing. 2
- dHow Dynamic Programming is empl oyed in parsing algorithms? 2
- eDiscuss the limitations of supe rvised approaches in handling W SD challenges
- fHow do semantic attachments cont ribute to disambiguating word senses?
- gDiscuss the applications of filter bank methods in speech sign al processing
- hHow do filter banks contribute to speech analysis? 2 i. Describe the role of Perceptual Linear Prediction. 2 j. How does the process of feature extraction contribute to under standing speech patterns?
Section BAttempt any three o f t h e f o l l o w i n g : 10 x 3 = 30
- aProvide an overview of Hidden Markov Models and Maximum Entr opy models in word-level analysis. How do these models contribute t o language processing tasks, and what are their strengths and weaknesses?
- bDiscuss Probabilistic CYK pars ing and Probabilistic Lexicalized CFGs. How do these probabilistic parsing techniques improve upon traditional parsing algorithms, and what are their applications in natural language processing?
- cCompare and contrast first-order logic with propositional lo gic. Discuss the expressive power of first- order logic and its significance in representing complex relationships
- dAnalyze the challenges associated with accurately representi ng and classifying speech sounds. How do these challenges impact the development of speech reco gnition systems?
- eExplain the significance of Li kelihood Distortions in speech analysis and how they contribute to the assessment of speech models
Section CAttempt any one p a r t o f t h e f o l l o w i n g : 10 x 1 = 10
- aExplain the concept of Minimum Edit Distance and its signifi cance in the context of word-level analysis
- bDiscuss the challenges associ ated with evaluating N-grams and the role of smoothing techniques
- aCompare and contrast Dependency Grammar with Phrase Structur e Grammar. Highlight the key diffe rences in representing syntacti c relationships between words in these two grammatical frameworks
- bHow does Shallow Parsing differ from deep parsing, and what are the advantages and limitations of each approach?
- aExamine how thesaurus-based and distributional methods contribute to measuring word similarity. Discus s the strengths and weaknesses o f each approach and their applicability in different contexts
- bCompare and contrast WSD techniques using dictionaries and t hesauri. How do these lexical resources c ontribute to disambiguating wor d senses, and what are the considerations when choosing between them?
- aExplore the acoustic phonetics aspect of speech production. How do the acoustics of speech production contribute to the perceptual dif ferences between various speech sounds?
- bExplore the Linear Predictive Coding method in speech proces sing. How does LPC model speech signals, and what are its advantages in speech analysis and synthesis?
- aElaborate on the concept of time alignment in speech analysi s, focusing on the techniques of Dynamic Time Warping and the representatio n of multiple time-alignment paths
- bExplain the process of evaluating Hidden Markov Models, incl uding the concept of the Optimal State Sequence and the role of Viterbi Search in determining the most likely sequence of states
Question text is extracted from the official AKTU question paper PDF above. Hindi translations are omitted — every question is printed in English in the original paper. Last verified: 2026-08-23.
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