PROFESSIONAL ELECTIVES
Electives in Artificial Intelligence
| Course Name | Conversational AI |
| Course Code | 23CSE476 |
| Program | B. Tech. in Computer Science and Engineering (CSE) |
| Credits | 3 |
| Campus | Amritapuri ,Coimbatore,Bengaluru, Amaravati, Chennai |
Electives in Artificial Intelligence
Introduction to Conversational AI, Principles of dialogue – common ground, sub dialogues, Gricean principles of conversation, Computational models of dialogue systems, Chatbots architectures – Rule-based and Corpus based, Case study: Sounding board
Architecture for dialogue systems: Pipelines behind common assistant programs, collaborative problem-solving model, dialogue acts. cognitive architectures, Question Answering: Sources of knowledge, Case Study: IBM’s Deep Q/A approach
Dialog Management and System Evaluation, Dialog Manager Architectures, Natural Language Generation, evaluation of performance, reward propagation. Case study: Social chatbot evaluation
Course Objectives
Course Outcomes
CO1: Understand computational models of dialogue systems.
CO2: Understand architectures for building conversational systems.
CO3: Apply problem-solving dialogue model for question answering.
CO4: Analyze dialogue management and chatbots.
CO-PO Mapping
| PO/PSO | PO1 | PO2 | PO3 | PO4 | PO5 | PO6 | PO7 | PO8 | PO9 | PO10 | PO11 | PO12 | PSO1 | PSO2 |
| CO | ||||||||||||||
| CO1 | 3 | 2 | 2 | 2 | 1 | 0 | 0 | 2 | 3 | 2 | 0 | 0 | 3 | 3 |
| CO2 | 3 | 2 | 2 | 2 | 1 | 0 | 0 | 2 | 3 | 2 | 0 | 0 | 3 | 3 |
| CO3 | 3 | 3 | 3 | 3 | 3 | 0 | 0 | 2 | 3 | 2 | 0 | 0 | 3 | 3 |
| CO4 | 3 | 3 | 3 | 3 | 3 | 0 | 0 | 2 | 3 | 2 | 0 | 0 | 3 | 3 |
Evaluation Pattern: 70:30
| Assessment | Internal | End Semester |
| Midterm | 20 | |
| Continuous Assessment – Theory (*CAT) | 10 | |
| Continuous Assessment – Lab (*CAL) | 40 | |
| **End Semester | 30 (50 Marks; 2 hours exam) |
*CAT – Can be Quizzes, Assignments, and Reports
*CAL – Can be Lab Assessments, Project, and Report
**End Semester can be theory examination/ lab-based examination/ project presentation
Textbook(s)
Seminck, O., Michael McTear.“Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots”, Computational Linguistics, 2023.
Reference(s)
Tur, G. and De Mori, R., “Spoken language understanding: Systems for extracting semantic information from speech”. John Wiley & Sons. 2011.
Jokinen, K. and McTear, M., “Spoken dialogue systems. Synthesis Lectures on Human Language Technologies”, vol. 2, no. 1, 2009.
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