CW3002 Conversational Systems Syllabus:
CW3002 Conversational Systems Syllabus – Anna University Regulation 2021
COURSE OBJECTIVES:
Enable attendees to acquire knowledge on chatbots and its terminologies
Work with ML Concepts and different algorithms to build custom ML Model
Better understand on Conversational experiences and provide better customer experiences
UNIT I FUNDAMENTALS OF CONVERSATIONAL SYSTEMS
Introduction: Overview, Case studies, Explanation about different modes of engagement for a human being, History and impact of AI. Underlying technologies: Natural Language Processing, Artificial Intelligence and Machine Learning, NLG, Speech-To-Text, Text-To-Speech, Computer Vision etc. Introduction to Top players in Market – Google, MS, Amazon &Market trends. Messaging Platforms (Facebook, WhatsApp) and Smart speakers – Alexa, Google Home and other new channels. Ethical and Legal Considerations in AI Overview.
UNIT II FOUNDATIONAL BLOCKS FOR PROGRAMMING AND NATURAL LANGUAGE PROCESSING
Introduction: Brief history, Basic Concepts, Phases of NLP, Application of chat bots etc. General chatbot architecture, Basic concepts in chatbots: Intents, Entities, Utterances, Variables and Slots, Fulfillment. Lexical Knowledge Networks (WordNet, Verbnet, PropBank, etc). Lexical Analysis, Part-of-Speech Tagging, Parsing/Syntactic analysis, Semantic Analysis, Word Sense Disambiguation. Information Extraction, Sentiment Analysis.
UNIT III BUILDING A CHAT BOT / CONVERSATIONAL AI SYSTEMS
Fundamentals of Conversational Systems (NLU, DM and NLG) – Chatbot framework & Architecture, Conversational Flow & Design, Intent Classification (ML and DL based techniques), Dialogue Management Strategies, Natural Language Generation. UX design, APIs and SDKs, Usage of Conversational Design Tools. Introduction to popular chatbot frameworks – Google Dialog flow, Microsoft Bot Framework, Amazon Lex, RASA Channels: Facebook Messenger, Google Home, Alexa, WhatsApp, Custom Apps. Overview of CE Testing techniques, A/B Testing, Introduction to Testing Frameworks – Botium /Mocha ,Chai. Security & Compliance – Data Management, Storage, GDPR, PCI.
UNIT IV ROLE OF ML/AI IN CONVERSATIONAL TECHNOLOGIES AND CONTACT CENTERS
Brief Understanding on how Conversational Systems uses ML technologies in ASR, NLP, Advanced Dialog management, Language Translation, Emotion/Sentiment Analysis, Information extraction ,etc. to effectively converse, Introduction to Contact centers – Impact & Terminologies. Case studies & Trends, How does a Virtual Agent/Assistant fit in here?
UNIT V CONVERSATIONAL ANALYTICS AND FUTURE
Conversation Analytics : The need of it – Introduction to Conversational Metrics – Summary, Robots and Sensory Applications overview – XR Technologies in Conversational Systems , XRCommerce – What to expect next? – Future technologies and market innovations overview.
COURSE OUTCOMES:
CO1: Familiarize in the NLTK tool kit and the pre-processing techniques of natural language processing.
CO2: Familiarize with the basic technologies required for building a conversational system.
CO3: Build a Chabot for any application and deploy it
CO4: Involve AI in building conversational system and build advanced systems that can be cognitively inclined towards human behaviour.
CO5: Build a real time working conversational system for social domain that can intelligently process inputs and generate relevant replies.
TOTAL :45 PERIODS
TEXTBOOKS:
1. Michael McTear, “Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots”, Second Edition, Moran and Claypool Publishers, 2020.
2. Cathy Pearl, “Designing Voice User Interfaces: Principles of Conversational Experiences”, O’REILLY, 2016.