Born-digital, dual-channel conversational audio in the accents Big Tech hasn't covered. Pidgin, Yoruba, Swahili, Zulu and more, verified by native-speaker editors, zero PII by design, ready for your training pipeline.
The world's most spoken languages are also the most under-served in training data. Voice-to-voice models fumble the moment they meet a Nigerian customer or a Nairobi merchant. That gap is a supply problem, and it's what we build.
Everyone builds voice agents. Almost no one builds them for accents outside Silicon Valley. Legacy call-center data is dirty and PII-laden. Common Voice is single-utterance and monotone. What labs need, real conversational, dual-channel, dialectal audio, barely exists at scale.
We generate it born-digital: gamified crowd, native-speaker verification, word-level alignment on tap.
Voice AI trained only on English and Mandarin structurally excludes most of the world. Local-language voice data doesn't just improve accuracy. It defines whether entire populations can use your product at all.
Adults globally with limited literacy. 77% live in Sub-Saharan Africa and Central/Southern Asia. Voice is their only route into AI.
African languages, most primarily spoken, not written. Text-first AI excludes them by design.
Older adults are twice as likely to use voice assistants (51%) as text chatbots. Voice reads as natural, screens as intimidating.
Global voice AI market projected by 2030. Non-Western coverage is the biggest unclaimed slice.
Same product, same launch budget. One trained only on English, one trained on the country's spoken languages alongside it. The difference is not a rounding error, it is a different company.
market expansion in Nigeria alone. Add Nigerian Pidgin, Yoruba, Igbo and Hausa and every excluded speaker becomes a served customer. Layer more countries and the math compounds.
Conservative addressable-market estimates. Sources: UN World Population Prospects 2024 · EF English Proficiency Index 2024 · World Bank adult literacy data · UNESCO Institute for Statistics · WHO Global Report on Health Equity for Persons with Disabilities · Grand View Research, voice AI market
Africans aged 60+ by 2030. Screen-averse, voice-native, the largest healthcare cost centre.
Adults across Africa and South Asia with limited literacy. Voice is their only interface, in their own language.
People globally with a significant disability (WHO). Voice-first is a primary access modality.
Of Africa is under 25. Voice-native from TikTok and WhatsApp, with zero patience for an agent that doesn't get their accent.
Same line, two takes. First, a state-of-the-art voice model attempting it. Then a native speaker from our studio. Watch the words light up as they're spoken.
Every session is a small production. Two players improvise from a card in their own language, a trained linguist verifies the transcript, and an audit layer samples everything behind them.
Two anonymously paired native speakers play a scene from a card authored in the target language by a linguist, presented as audio with text as a fallback: a fraud dispute, a market haggle, a KYC call. Nothing is translated from English, so the speech is native, not calqued. Each voice records to its own channel.
output · raw dual-channel audioEditors are recruited, trained and certified language professionals, not players. Each transcript is verified by one of them, with an English gloss written downstream from what was actually said, and slang, code-switches and tone tags corrected. Peer ratings below 4 force a retake before anything ships.
output · verified transcript + labelsSessions are chunked, indexed and hashed, with word-level alignment as a tier option. Every session manifest records its prompt_direction, target-native by default or English-anchored on request. A 30% random audit re-reviews turns blind. Anything that fails is reworked or dropped, never shipped.
A reference delivery bundle showing exactly what a buyer receives, with synthetic sessions: 10 sessions, 118 turns across 6 locales, schema reference, indicative evaluation baselines and the consent register. Audio ships on request.
PDF · 46 pages · 2.7 MB · no email required
Every translated span links back to its English source, typed by phenomenon. Serial verbs, aspect shifts, null particles, the constructions that make these languages hard, mapped for you.
Production is commissioned against a signed order, not pulled from stock. Non-exclusive by default, exclusivity available and priced. Deposit on signature, balance on delivery or in milestones. We quote a lead time and a sustained weekly rate per language from measured throughput.
A scoped bundle in your target locale and domain, sized for a fine-tune experiment. Commissioned on signature; a standing Nigerian Pidgin corpus lets a Pidgin pilot ship within days.
one-off · evaluation friendlyA monthly flow of fresh verified hours in the locales you pick. Same schema, versioned releases, replacement SLA.
recurring · volume pricedYour scenarios, personas and edge cases, authored into target-language scenario cards by our linguists. Recruited, interviewed speakers play your test set into existence.
directed · your IP guardrailsEverything above plus word-level alignment, typed by linguistic phenomenon and confidence scored. English-anchored prompting available per order for source-anchored parallel data, recorded per session.
tier 4 · translation gradePer-speaker signed agreement, SHA-256 anchored, withdrawal SLA
GDPR, NDPA and POPIA aligned, PII redacted at capture
AES-256 at rest, TLS 1.3 in transit, IP-whitelisted delivery
Type II program in progress with a Big Four auditor
Born-digital, zero scraped audio, full chain of custody
Every player signs this before their first paid recording: a plain-language summary, explicit biometric consent as a separate act, what licensees may never do, withdrawal, retention, transfers, and the consent record whose fingerprint travels inside every session you receive.
Download the agreement ↓The EDPB Guidelines 05/2020 criteria for valid consent, each with the clause that satisfies it.
Self-assessment by Accent Studio against a published standard, v1.0. External attestations will be listed here as they complete. Not legal advice.
We'll come back within one business day with a sample bundle, a schema walkthrough and an honest read on fit.
