Bilingual text dataset for multilingual speech models
Delivering 300K+ validated words across 10 low-resource languages and 4 scripts within a 14-day window.
Client Context & Operational Challenge
A global AI research organization building multilingual speech recognition models needed validated bilingual text data across 10 low-resource languages spanning South Asia, Southeast Asia, and the Pacific — languages where qualified linguists are scarce, standardized orthographies are contested, and no ready-made contributor supply chain exists.
Execution & Governance Model
Triaged languages into three sourcing tiers based on contributor availability. Tier 1: recruited through professional linguist networks. Tier 2: sourced via academic departments and regional university partnerships with custom qualification testing. Tier 3: discovered through diaspora networks and cultural preservation organizations with bespoke qualification exams built by internal linguists. Each contributor completed a paid qualification task graded against reference translations. Pilot phase processed 2,000 words per language to calibrate quality expectations and build starter glossaries. Production organized into five staggered delivery batches over eleven days across all languages in parallel.
Scale & Velocity Constraints
- 10 low-resource languages across Austronesian, Indo-Aryan, and Semitic families
- 4 distinct scripts including competing romanization conventions
- Fewer than 20 known qualified transcribers globally for certain target languages
- Fixed quarterly model-training intake deadline with no schedule flexibility
- Significant dialectal variation requiring precise register selection per language
What Was Delivered
Asset Outputs & Deliverables
- Delivered 300,000+ validated words across 10 languages and 4 scripts within the 14-day window. Post-delivery revisions under 1.5%. Glossaries and style guides created from scratch for 6 languages. Vetted contributor pool of 35+ rare-language specialists retained for follow-on phases. Client data passed internal model-readiness validation on first submission for 8 of 10 languages.
Operational Footprint
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