Conversational agents have evolved beyond basic pre-programmed chat-flow trees. Modern assistants leverage generative AI and speech-to-text models to hold intelligent, context-aware conversations via text or voice.
Architecture of a Conversational Agent
A modern AI assistant comprises three core components:
- Speech Recognition (STT): Transcribing voice inputs into text strings in real-time.
- Natural Language Processing (NLP/LLM): Interpreting user intent, loading background database records, and drafting a contextual response.
- Text-to-Speech (TTS): Converting responses back into high-quality, human-like voice audio.
Implementing system-wide state trackers allows assistants to remember details from earlier in the conversation, resulting in smooth, highly personalized customer support flows.
