Detailed Units:
Syllabus
UNIT - I: Introducing Dialogue Systems
- Foundations: Introduction to Dialogue Systems and their evolution.
- History: The lineage of Conversational AI from early iterations to modern tech.
- State of the Art: Overview of Present-Day Dialogue Systems.
- Modeling & Design: * Conceptualizing Conversation Dialogue Systems.
- Best practices for Designing and Developing Dialogue Systems.
UNIT - II: Rule-Based Dialogue Systems: Architecture, Methods, and Tools
- System Design: Understanding Dialogue Systems Architecture.
- Development Workflow: Designing a Dialogue System from the ground up.
- Tech Stack: Tools and frameworks for developing Rule-Based systems.
- Case Study: Rule-Based Techniques in Dialogue Systems participating in the Alexa Prize.
UNIT - III: Statistical Data-Driven Dialogue Systems
- Approach: Motivating the shift toward Statistical Data-Driven models.
- Core Components: Dialogue components within the statistical framework.
- Decision Processes:
- Reinforcement Learning (RL) fundamentals.
- Representing Dialogue as a Markov Decision Process (MDP).
- Transitioning from MDPs to POMDPs (Partially Observable MDPs).
- Management: * Dialogue State Tracking (DST).
- Dialogue Policy optimization.
- Challenges and issues with RL in POMDP environments.
UNIT - IV: Evaluating Dialogue Systems
- Evaluation Metrics: The process and methodology of evaluation.
- System Types:
- Evaluating Task-Oriented Dialogue Systems.
- Evaluating Open-Domain Dialogue Systems.
- Frameworks: * PARADISE Framework.
- Quality of Experience (QoE) and Interaction Quality.
- Synthesis: Determining the best practices for comprehensive system evaluation.
UNIT - V: End-to-End Neural Dialogue Systems
- Neural Modeling: Introduction to Neural Network approaches in dialogue.
- Architectures:
- Neural Conversational Models.
- Retrieval-Based vs. Generative Response Generation.
- Applications:
- Task-Oriented Neural Dialogue Systems.
- Open-Domain Neural Dialogue Systems (Chatbots).
- Current Landscape: * Contemporary issues and existing solutions.
- Datasets, Competitions, Tasks, and Challenges in the field.
Based on:
and
*Google Gemini’s Summarization*