Natural Language Processing
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Follow on Instagram for UpdatesNatural Language Processing Syllabus — Unit-wise Content
The official GTU curriculum for Natural Language Processing (subject code 3174808) as prescribed for CS-Cyber · Semester 7 divides the course into 6 units, covering 42 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (3174808)Unit 1 Introduction
- Origins and challenges of nlp – language modeling: grammar-based lm, statistical lm – regular expressions
- finite-state automata – english morphology
- transducers for lexicon and rules
- detecting and correcting spelling errors
- minimum edit distance
Unit 2 Word Level Analysis
- Unsmoothed n-grams
- evaluating n-grams
- interpolation and backoff – word classes
- part-of-speech tagging
- stochastic and transformation-based tagging
- issues in pos tagging – hidden markov and maximum entropy models
Unit 3 Syntactic Analysis
- Context free grammars
- grammar rules for english
- normal forms for grammar – dependency grammar – syntactic parsing
- dynamic programming parsing – shallow parsing – probabilistic cfg, probabilistic probabilistic lexicalized cfgs – feature structures
- unification of feature structures
Unit 4 Semantics And Pragmatics
- Requirements for representation
- first-order logic
- description logics – syntax-driven semantic analysis
- semantic attachments – word senses
- relations between senses
- thematic roles
- selectional restrictions – word sense disambiguation
- using supervised
- dictionary & thesaurus
- bootstrapping methods – word similarity using thesaurus and distributional methods. 06 Program Name: Bachelor of Engineering Level: UG Subject Code : 3174808 Subject Name : Natural Language Processing w.e.f. 2025-26 http://syllabus.gtu.ac.in/ Page no. 1 of
Unit 5 Basic Concepts of Speech Processing
- Speech fundamentals: articulatory phonetics – production and classification of speech sounds
- acoustic phonetics – acoustics of speech production
- review of digital signal processing concepts
- short-time fourier transform
- filter- bank and lpc methods
Unit 6 Speech-Analysis,Speech Modeling
- feature extraction and pattern comparison techniques: speech distortion measures– mathematical and perceptual – log–spectral distance
- cepstral distances
- weighted cepstral distances and filtering
- likelihood distortions
- spectral distortion using a warped frequency scale coefficients
- time alignment and normalization – dynamic time warping
- multiple time – alignment paths
- Hidden markov models: markov processes– evaluation
- optimal state sequence – viterbi search
- baum-welch parameter re-estimation
- implementation issues
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