GenAI - High-Quality Voice Data Collection for AI - Virtual Assistant Training

SUMMARY

Oprimes partnered on a voice data collection project to train virtual assistants in understanding Hindi. The team delivered 150 high-quality submissions across two phases, capturing diverse accents and pronunciations from various regions. With strict quality checks and participant support, the project enabled the client to build a robust and ethical Hindi voice dataset. The result was improved AI accuracy and readiness for real-world use.

THE CHALLENGE

• Managing clarity between rural and urban Hindi pronunciations.
• Minimizing background noise in a remote, crowd-sourced setup.
• Training first-time users on proper voice recording techniques (WAV, Mono, 16kHz).
• Scaling participant onboarding without compromising quality.

SOLUTION

• Targeted Participant Sourcing from diverse Hindi-speaking regions.
• Manual QA by Linguistic Experts to ensure clarity and accuracy.
• Tech-Driven Workflow using oprimes, dashboards, and chat support.
• Streamlined Onboarding & Consent for smooth, compliant participation.
• Real-Time Support to guide contributors and reduce errors.

KEY OUTCOMES

• Delivered 150 successful voice submissions with 20,000+ reviewed audio files.
• Built a linguistically diverse Hindi dataset for virtual assistant training
• Achieved zero data breaches or consent violations.
• Reduced rework rates and enhanced recording quality in the scaled phase.