(SEM V) THEORY EXAMINATION 2024-25 NATURAL LANGUAGE PROCESSING
Course: B.Tech (Semester V)
Subject: Natural Language Processing
Subject Code: BCAI052
Maximum Marks: 70
Time: 3 Hours
Paper ID: 310316
Section A (2 × 7 = 14 Marks)
Answer all questions briefly:
Write various limitations of Natural Language Processing.
Differentiate between top-down and bottom-up parsers.
Discuss the concept of Knowledge Representation and Knowledge Base.
What are the limitations of Probabilistic Context-Free Grammars (PCFGs)?
Write the concept of Phonetics and list its main branches.
Discuss the applications of filter bank methods in speech signal processing.
What does discourse planning involve?
Section B (Attempt any three × 7 = 21 Marks)
Explain Add-k smoothing and discuss methods for evaluating N-grams.
Provide an algorithm for a basic top-down parser with an example.
Describe thesaurus-based and distributional word similarity methods with their advantages.
Explain the concept of Digital Signal Processing.
Discuss parallelization and batch processing techniques, and compare both in the context of NLP.
Section C (Long Answer Questions – 7 Marks each)
Q3
(a) Provide a pseudo-code algorithm for parsing a Finite-State Transducer and explain with an example,
OR
(b) Explain Zipf’s Law and how it is applied in NLP.
Q4
(a) Explain Augmented Grammars and Lexicon in NLP,
OR
(b) For CFGs (S → NP VP, VP → V NP, NP → Det N), draw a Shift-Reduce Parser for the sentence:
“The woman saw a puppy.”
Lexical entries:
The, a → Det
Woman, puppy → N
Saw → V
Q5
(a) Explain the relationships between word senses and knowledge sources used in Word Sense Disambiguation (WSD),
OR
(b) Explain Thematic Roles in semantic analysis and their applications.
Q6
(a) Explain vowels, semi-vowels, diphthongs, and consonants in relation to Speech Recognition Systems,
OR
(b) Explain Linear Predictive Coding (LPC) — how it models speech signals and its benefits in speech analysis and synthesis.
Q7
(a) Explain the Hidden Markov Model (HMM) with Baum-Welch parameter re-estimation and its implementation issues,
OR
(b) Describe the concept and process of Chatbots with an example.
Important Topics for Revision
Limitations & Scope of NLP
Parsing Techniques (Top-Down, Bottom-Up, Shift-Reduce)
Knowledge Representation, PCFG, and Lexicon
Word Sense Disambiguation (WSD)
Phonetics and Speech Signal Processing
Hidden Markov Models & Chatbots
Parallelization and Batch Processing in NLP
Digital Signal & Speech Processing Concepts
Related Notes
BASIC ELECTRICAL ENGINEERING
ENGINEERING PHYSICS THEORY EXAMINATION 2024-25
(SEM I) ENGINEERING CHEMISTRY THEORY EXAMINATION...
THEORY EXAMINATION 2024-25 ENGINEERING MATHEMATICS...
(SEM I) THEORY EXAMINATION 2024-25 ENGINEERING CHE...
(SEM I) THEORY EXAMINATION 2024-25 ENVIRONMENT AND...
Need more notes?
Return to the notes store to keep exploring curated study material.
Back to Notes StoreLatest Blog Posts
Best Home Tutors for Class 12 Science in Dwarka, Delhi
Top Universities in Chennai for Postgraduate Courses with Complete Guide
Best Home Tuition for Competitive Exams in Dwarka, Delhi
Best Online Tutors for Maths in Noida 2026
Best Coaching Centers for UPSC in Rajender Place, Delhi 2026
How to Apply for NEET in Gurugram, Haryana for 2026
Admission Process for BTech at NIT Warangal 2026
Best Home Tutors for JEE in Maharashtra 2026
Meet Our Exceptional Teachers
Discover passionate educators who inspire, motivate, and transform learning experiences with their expertise and dedication
Explore Tutors In Your Location
Discover expert tutors in popular areas across India
Discover Elite Educational Institutes
Connect with top-tier educational institutions offering world-class learning experiences, expert faculty, and innovative teaching methodologies