Voqals
Ground Truth For Indian Speech AI
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Aditya Raghav

Voqals - Ground Truth For Indian Speech AI

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Most Indian speech datasets are scraped, noisy, and poorly annotated. Voqals does it differently — we studio-record real code-switched conversations (Hindi-English, Tamil-English, etc.) with professional voice talent, then deliver SFT-ready datasets with ground-truth annotations built in. Same methodology used by the world's biggest AI labs, now available for any team building Indian language ASR, TTS, or conversational AI. Custom collection in any Indian language, any domain.

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Aditya Raghav
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Hey Product Hunt! I'm Aditya, founder of Voqals. I spent 8 years building speech datasets for some of the world's largest tech companies and saw firsthand how the biggest AI models get their training data. The problem? That entire methodology barely exists for Indian languages. Most teams building Indian speech AI are stuck with scraped audio, inconsistent annotations, and data that doesn't reflect how Indians actually talk — we code-switch constantly, mixing Hindi with English or Tamil with English mid-sentence. Voqals fixes this. We studio-record natural, code-switched Indian speech with professional talent, and every recording comes with ground-truth annotations by design — not guessed after the fact. The same source gives you both clean audio for TTS and realistic, chaotic audio for ASR/NLU. We're starting with Hindi-English and scaling to every major Indian language. Would love to hear from anyone working on Indian language AI — what's been your biggest data pain point?