Inside a Production Voice Architecture for Igbo, Yoruba, and Hausa
Building a real-time voice chatbot for African languages is not about swapping language codes in a cloud API. Hausa, Yoruba, and Igbo are severely underrepresented in every major commercial model — Whisper hallucinates on silence, NLLB mistranslates common Yoruba phrases, and off-the-shelf TTS has never heard Igbo spoken. This article walks through how we built and deployed a production pipeline serving all four languages (English, Hausa, Yoruba, Igbo), every component fine-tuned and running behind an OpenAI-compatible API.
The Architecture
Five independent microservices, each owning one concern:
Every service exposes an OpenAI-compatible HTTP endpoint. The chatbot calls them with the same openai Python client it would use for GPT-4, just with a different base_url. Swapping or scaling any component requires no application code changes.
Speech-to-Text: Fine-Tuned Whisper + Silero VAD
The base whisper-small-multilingual checkpoint produces 30–40% WER on Hausa without fine-tuning. After fine-tuning on approximately 50 hours of native speaker audio...
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