Research
Featured Research Projects
Vociply: Real-Time Voice AI System
A groundbreaking voice-to-voice agentic system that combines large language models with real-time speech processing to automate business conversations in multiple African languages.
Research Contributions:
- Novel architecture bridging LLMs with speech processing
- Creative solutions for multilingual data scarcity
- Real-time optimization for voice-based AI agents
- Production-scale deployment of research prototypes
Technical Highlights:
- End-to-end voice processing pipeline
- Multilingual natural language understanding
- Real-time response generation (<200ms latency)
- Scalable cloud infrastructure
Hypernetwork Optimization Framework
Investigating how hypernetworks can optimize ternary neural networks for efficient edge AI deployment, addressing the critical need for AI democratization in resource-constrained environments.
Research Contributions:
- Can hypernetworks improve ternary network training efficiency?
- What are the optimal architectures for edge AI deployment?
- How can we balance accuracy with computational constraints?
Technical Highlights:
- More efficient AI models for mobile and IoT devices
- Reduced computational requirements for AI applications
- Broader accessibility of advanced AI technologies
Multilingual Voice AI Research
Pioneering research in voice AI systems that work effectively across African languages, addressing fundamental challenges in low-resource language processing.
Research Contributions:
- Data augmentation for speech data scarcity
- Transfer learning across related languages
- Cultural and linguistic adaptation in AI systems
- Community-driven dataset development
Conference Participation
Deep Learning Indaba 2025
Africa • 2025
AMLD Africa 2024
USIU Kenya • 2024
Publications & Academic Output
Vociply: A Real-Time Voice-to-Voice Agentic System for African Business Automation Using LLMs
Maroa, C. et al.
Deep Learning Indaba 2025 [Accepted]
View PaperHypernetwork Optimization of Ternary Neural Networks for Edge AI Deployment
Maroa, C. et al.
Research Draft [Draft]
Research Pipeline
- Edge AI democratization tools and methodologies
- Multilingual conversational AI architectures
- Audio processing optimization techniques
- Human-AI interaction paradigm studies
Open Source Contributions
Edge AI Optimization Tools
Open-source utilities for deploying efficient ML models on ARM-based devices, democratizing AI deployment capabilities.
Features:
- Model compression utilities
- Performance benchmarking tools
- Deployment automation scripts
- Educational resources and tutorials
AI Learning Resources
Comprehensive learning paths and documentation bridging academic ML research with practical implementation.
Features:
- Workshop materials and tutorials
- Code examples and best practices
- Mentorship programs for emerging researchers
- Technical documentation and guides