Feedback-Based Self-Learning in Large-Scale Conversational AI Agents

Understand

Today, most large-scale conversational AI agents (e.g.

• Alexa, Siri, or Google Assistant) are built using manually annotated data to train the different components of the system.
• Typically, the accuracy of the ML models in these components are improved by manually transcribing and annotating data.
• As the scope of these systems increase to cover more scenarios and domains, manual annotation to improve the accuracy of these components becomes prohibitively costly and time consuming.