Key Components of Conversational AI

1. Natural Language Understanding (NLU)

• Enables AI to comprehend user inputs, extract intents, and recognize entities.
• Uses NLP techniques like tokenization, named entity recognition (NER), and syntactic parsing.

2. Natural Language Generation (NLG)

• Produces human-like responses based on context and user queries.
• Ensures responses are coherent, relevant, and grammatically correct.

3. Dialogue Management

• Handles the flow of conversation by deciding how the AI should respond.
• Maintains context across multi-turn conversations.

4. Speech Recognition and Synthesis

• Converts spoken language into text (ASR - Automatic Speech Recognition).
• Synthesizes text into natural-sounding speech (TTS - Text-to-Speech).

5. Machine Learning Models

• Trains models to improve conversation quality over time.
• Includes both rule-based and deep learning-based approaches like transformers (e.g., GPT, BERT).