Voice-Powered Study Agent

Building a Voice-Powered Study Agent with ElevenLabs

I’ve been experimenting with AI tools for a while now, and one area that’s always fascinated me is how we can use AI to enhance learning. Recently, I built a voice-powered study agent using ElevenLabs’ conversational AI capabilities, and I wanted to share my experience and insights from this project.

The Problem: Studying on the Go

Like many of you, I’m constantly trying to maximize my learning time. My daily commute to work offers a perfect opportunity for study, but traditional methods have limitations:

1. Safety first - I can’t (and shouldn’t) be reading or watching videos while driving
2. Passive consumption - Just listening to audio books or lectures doesn’t engage my brain actively enough
3. Lack of structure - Using OpenAI’s advanced chat is great, but it requires me to constantly guide the conversation

What I needed was a solution that would allow me to study hands-free, engage actively with the material, and provide a structured learning experience without requiring constant input from me.

The Solution: AudioAnkiCards

This led me to create AudioAnkiCards, a voice-powered study agent that combines the principles of spaced repetition learning with conversational AI.

AudioAnkiCards Interface

How It Works

The system is built on several key technologies:

1. ElevenLabs Conversational AI - Provides the voice interface and natural conversation capabilities
2. Spaced Repetition Learning - Based on the principles that made Anki flashcards so effective
3. Railway.app - For hosting and deployment of the application

The agent works by: - Presenting questions in audio format during my commute - Listening to my responses - Providing immediate feedback on my answers - Adjusting the frequency of questions based on my performance (spaced repetition)

Why This Approach Works

If you’re familiar with learning science, you’ll know that active recall is one of the most effective ways to cement knowledge in your long-term memory. As the Anki documentation explains:

Active recall testing means being asked a question and trying to remember the answer. This is in contrast to passive study, where we read, watch, or listen to something without pausing to consider if we know the answer. Research has shown that active recall testing is far more effective at building strong memories than passive study.

By combining this principle with voice technology, I’ve created a hands-free learning system that engages my brain actively during otherwise “dead” time.

Technical Implementation

The system uses ElevenLabs’ conversational AI platform, which combines several powerful components:

• Speech to text - Transcribes my spoken responses
• Language model - Processes the conversation and generates appropriate responses
• Text to speech - Converts the AI’s responses into natural-sounding speech
• Turn taking - Manages the conversation flow naturally

ElevenLabs makes this relatively straightforward to implement, as they’ve done the hard work of integrating these components into a cohesive platform.

Future Developments

While the current system is already useful, I have several ideas for future enhancements:

1. Performance assessment - Using an agent to evaluate how well I’ve answered questions and provide more detailed feedback
2. Dynamic question generation - For topics I struggle with, automatically generating new questions to reinforce learning
3. Content retrieval - Integrating with books, articles, or other content to automatically generate questions from material I want to learn

These enhancements would make the system even more powerful as a learning tool, essentially creating an AI tutor that adapts to my learning needs.

Lessons Learned

Building this project has taught me several valuable lessons:

1. Voice interfaces are powerful for learning - They engage different cognitive pathways than text
2. Structured agents are more effective than free-form chat - Having a specific purpose and format makes the learning more focused
3. Spaced repetition principles work well with AI - The algorithmic nature of spaced repetition pairs naturally with AI systems

Try It Yourself

If you’re interested in trying out AudioAnkiCards, you can visit https://audioankicards-production.up.railway.app/ to see it in action.

I’d love to hear your thoughts and suggestions for how to improve this system. Have you built similar learning tools? What approaches have you found most effective?

Resources

If you want to explore this area further, here are some resources I found helpful:

• ElevenLabs Conversational AI Documentation
• Anki and Spaced Repetition Learning
• Retrieval-Augmented Generation (RAG) for Learning Systems

Let me know in the comments if you have questions about implementing something similar!