🎙️ Swahili voice AI — speech-to-text, text-to-speech, and voice-first interfaces for low-literacy East African users
# 🎙️ Ongea AI — Swahili Voice AI
> *Ongea* (Swahili) = speak, talk, converse
Voice-first AI interface for Swahili speakers — speech-to-text, text-to-speech, and conversational AI for users who read slowly or not at all. Designed for low-literacy East African users who interact best by voice.
## Why Voice Matters
30% of Kenyan adults read below primary school level. But virtually all own a mobile phone and can speak and listen. Voice AI removes the literacy barrier — users speak their question in Swahili and hear the answer. No typing, no reading, no language barrier.
## Architecture
```
User speaks (Swahili)
→ Whisper (speech-to-text)
→ Gemini (reasoning in Swahili)
→ TTS (text-to-speech, Swahili)
→ User hears answer
```
## Use Cases
- 🌾 Farmer asks: "Je, leo ni wakati mzuri wa kupanda mahindi?"
- đź’Š Patient asks: "Dawa hii ninaitumia vipi?"
- đź’° Business owner: "Ninaweza kupata mkopo mdogo vipi?"
- đź“‹ Voter: "Namshinda nani mgombea katika kura yangu?"
## Quickstart
```bash
pip install -r requirements.txt
streamlit run app.py
```
## Research Basis
OpenAI Whisper (Radford et al. 2022) has documented support for Swahili. The voice-first interface pattern is validated by USSD and SMS mHealth research in East Africa (PMC10562967).
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*gabrielmahia.ai | Part of the Swahili AI Infrastructure Stack*