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AKTU Natural Language Processing (BAI052) Syllabus PDF – B.Tech 3rd Year
Natural Language Processing BAI052
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Official AKTU syllabus of Natural Language Processing (BAI052) for B.Tech 3rd Year – 3 credits, L-T-P 3-0-0. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — Natural Language Processing
Download PDFBAI052 · 3 credits · L-T-P 3-0-0
Course Outcomes
At the end of course , the student will be able :
| CO 1 | To learn the fundamentals of natural language processing | K , K 1 2 |
| CO 2 | To understand the use of CFG and PCFG in NLP | K , K 1 2 |
| CO 3 | To understand the role of semantics of sentences and pragmatic | K 2 |
| CO 4 | To Introduce Speech Production And Related Parameters Of Speech. | K , K 1 2 |
| CO 5 | To Show The Computation And Use Of Techniques Such As Short Time Fourier Transform, Linear Predictive Coefficients And Other Coefficients In The Analysis Of Speech. | K K 3, 4 |
Course Content
L-T-P: 3-0-0
| Unit | Topic | Proposed Lecture |
|---|---|---|
| I | 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, Tokenization, Detecting and Correcting Spelling Errors, Minimum Edit Distance WORD LEVEL ANALYSIS : Unsmoothed N-grams, Evaluating N-grams, Smoothing, Interpolation and Backoff – Word Classes, Word Tokenization,Math with words TF-IDF Vectors, Finding meaning in word count ( Semantic Analysis), Linguistic Background: Outline of English Syntax, Introduction to Semantics and Knowledge Representation,Zipf’s Law | 08 |
| II | SYNTACTIC ANALYSIS: Context Free Grammars, Grammar rules for English, Grammars and Parsing: Grammars and sentence Structure, Top-Down and Bottom-Up Parsers, Transition Network Grammars, Top- Down Chart Parsing. Feature Systems and Augmented Grammars: Basic Feature system for English, Morphological Analysis and the Lexicon, Parsing with Features, Augmented Transition Networks. Ambiguity Resolution: Statistical Methods, Probabilistic Language Processing, Estimating Probabilities, Part-of-Speech tagging, Obtaining Lexical Probabilities, Probabilistic Context-Free Grammars, Best First Parsing Feature structures, Unification of feature structures. | 08 |
| III | 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, WSD using Supervised, Dictionary & Thesaurus, Bootstrapping methods – Word Similarity using Thesaurus and Distributional methods. | 08 |
| IV | BASIC CONCEPTS of Speech Processing :Speech Fundamentals: Articulatory Phonetics – | 08 |
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.
| V | SPEECH-ANALYSIS: Features, Feature Extraction And Pattern Comparison Techniques: Speech Distortion Measures– Mathematical And Perceptual Real World NLP Challenges-Information Extraction and Question Answering,DialogEngines,Optimization,Parallelization and batch processing | 08 |
Text Books
- Daniel Jurafsky, James H. Martin―Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech, Pearson Publication, 2014.
- Steven Bird, Ewan Klein and Edward Loper, ―Natural Language Processing with Python, First Edition, OReilly Media, 2009.
- Lawrence RabinerAndBiing-Hwang Juang, “Fundamentals Of Speech Recognition”, Pearson Education, 2003.
- Daniel JurafskyAnd James H Martin, “Speech And Language Processing – An Introduction To Natural Language Processing, Computational Linguistics, And Speech Recognition”, Pearson Education, 2002.
- Frederick Jelinek, “Statistical Methods Of Speech Recognition”, MIT Press, 1997.
- 1. Breck Baldwin, ―Language Processing with Java and LingPipe Cookbook, Atlantic Publisher, 2015.
- Richard M Reese, ―Natural Language Processing with Java, OReilly Media, 2015.
- Nitin Indurkhya and Fred J. Damerau, ―Handbook of Natural Language Processing, Second Edition, Chapman and Hall/CRC Press, 2010.
- Tanveer Siddiqui, U.S. Tiwary, ―Natural Language Processing and Information Retrieval, Oxford University Press, 2008.
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