End-to-end audio data pipeline for Tagbana (Tagouana) indigenous language preservation — crowdsourced collection, peer validation, and ASR training data preparation
# Tagbana Speech Pipeline
An end-to-end audio data pipeline for indigenous language preservation, built to collect, validate, and prepare speech data for Automatic Speech Recognition (ASR) training — with a focus on Tagbana (Tagouana), a low-resource language with little to no existing digital speech data.
This project addresses a structural problem in ASR research: low-resource languages are underserved because clean, labeled training data is expensive and difficult to collect from native speaker communities. Tagbana Speech Pipeline solves this with a mobile-first, low-bandwidth collection workflow built around infrastructure communities already use — WhatsApp — paired with a native-speaker-driven validation layer that ensures data quality before it ever reaches a model.
## Live Demos
- 🎙️ **Speech Collector** →
huggingface.co
- ⚖️ **Speech Validator** →
huggingface.co
- 📊 **Dataset** →
huggingface.co
## Why This Exists
Most ASR research and tooling assumes the existence of large, clean, pre-labeled datasets — an assumption that excludes thousands of low-resource and indigenous languages from benefiting from modern speech technology. Tagbana Speech Pipeline is a reusable template for closing that gap: a crowdsourcing and peer-validation framework that any low-resource language community could adapt, not just a one-off dataset.
## Architecture
```
Native Speaker (WhatsApp)
│
▼
┌─────────────────────┐
│ Speech Collector │ Mobile-optimized web app
│ (collector/) │ 16kHz mono audio capture
└─────────┬────────────┘
│ raw audio + metadata
▼
┌─────────────────────┐
│ Speech Validator │ Peer-review interface
│ (validator/) │ Consensus-based validation
└─────────┬────────────┘
│ validated, clean audio
▼
┌─────────────────────┐
│ Secure Data Warehouse│
└─────────┬────────────┘
│
▼
ASR Fine-Tuning Rea …