As part of the Preply x Agora Hackathon: AI Agents for NextGen Language Learning, we've put together some thought starters to help you brainstorm and develop your project ideas. Each concept presents a unique challenge and an opportunity to push the boundaries of conversational AI technology.
Build a voice AI agent with Anam avatar and Thymia biomarkers that detects learner stress and anxiety during language practice. When the agent senses rising stress levels, it adjusts its pace, offers encouragement, and switches to easier material. The avatar provides a calming visual presence while biomarker data drives real-time adaptation.
Create a pronunciation coach that uses Thymia voice analysis to go beyond simple speech recognition. Track vocal confidence, detect frustration patterns, and identify when a learner is struggling with specific sounds. The agent provides targeted exercises and celebrates improvement using biomarker trends over the session.
Build a face-to-face language tutor using Anam video avatars that makes conversation practice feel natural. The avatar tutor speaks the target language, uses facial expressions to provide non-verbal feedback, and adapts lesson difficulty based on the learner's responses. Support multiple languages and cultural contexts.
Create an AI interview coach that helps job seekers practice professional conversations in their target language. Use Thymia biomarkers to track stress and confidence levels during mock interviews, providing feedback not just on what was said but how it was said — vocal clarity, hesitation patterns, and composure under pressure.
Build a conversational AI that simulates real-world scenarios — ordering at a restaurant, asking for directions, negotiating at a market — in the target language. The agent plays different characters, adjusts difficulty based on the learner's level, and provides cultural context alongside language corrections.
Create a system that tracks language learning sessions over time, analyzing conversation transcripts and Thymia biomarker data to visualize progress. Show metrics like vocabulary growth, fluency improvements, confidence trends, and optimal study times. The AI agent uses this data to personalize each session.
Build an AI agent that facilitates group language exchange sessions using Agora RTC for multi-party voice/video. The agent moderates conversations, suggests discussion topics, corrects errors in real-time, and ensures balanced participation. Use RTM for text-based vocabulary hints and corrections alongside the voice conversation.