AI data, evaluation and implementation under one accountable delivery model.
Contact us Become a ContributorYPAI collects, annotates and evaluates automotive speech in real cabin conditions. Native speakers. Dialect and accent coverage. HVAC, road and passenger overlap. Consent evidence and a QA package with the delivery.
Norwegian legal entity · EEA-based processing available · DPA per engagement
Languages available through the YPAI contributor and specialist network
Contributor network reach for native-speaker recruitment, not a mobilisation promise
Speaker recruitment and recording in the required language markets
Engine, HVAC, road surface, open windows, passenger overlap, music and device variation
Collection, annotation and evaluation work across OEM and Tier-1 voice programmes. Relationship and scope vary by engagement.
YPAI scopes the locales, dialects, speaker profiles and cabin acoustics that decide whether in-car speech still works on the road.
The brief can cover one acoustic or language gap, or the full chain from speaker recruitment through accepted annotation.
Speech collection programmes
Positive examples, confusable negatives, far-field cabin capture and accent variety.
Native-speaker recruitment against the target locales, regional varieties and buyer-defined age or speaking-style cohorts.
Highway and city noise, HVAC, open windows, device position and multi-passenger overlap recorded in real cabins.
Annotation and acceptance programmes
Locale, dialect, cabin, rights and acceptance requirements turn this scope into a speech-data specification.
Three ways to enter the same controlled delivery.
For a new locale, dialect set or cabin-microphone profile.
Turn speaker profiles, scripts, devices and acoustic requirements into a capture and annotation plan, then deliver an accepted corpus with the agreed metadata and labels.
For a system that fails on regional speech or real driving noise.
Use model outputs and failure cases to isolate gaps by locale, speaker profile or cabin condition, then define the right evaluation, review or targeted collection.
For a defined production brief, ready to execute.
Turn the specification, rights model and acceptance criteria into qualification, calibration, production, QA, review, rework and accepted batches.
The delivery plan takes shape around the actual speech work.
Align speaker profiles, devices, review criteria and capture protocol before production begins.
Prove the specification against submitted recordings, then use the accepted batch to set the working forecast.
Recruitment, capture, review, rework and replacement coverage move together against the programme brief.
The forecast uses the unit that matters to the programme: accepted speaker-hours, recordings, sessions or assets.
AI DATA & EVALUATION
Managed collection, annotation, validation and evaluation, with the evidence trail attached.
Not a contributor marketplace. A managed data operation with accountable delivery.
Scope an in-cabin speech programme
Road noise, HVAC, dialect and spontaneous speech change what must be collected and how recognition is judged.
For relevant YPAI-managed work, YPAI's Data Collection and Assurance Platform connects:
Reviewers and operations teams see the same task status and version history.
Failed recordings return for re-recording, rework, replacement or rejection according to the project rules.
Accepted material moves into versioned batches, manifests and secure delivery.
Role-based dashboard and client-portal access can be provided for YPAI-managed work.
The operating model can use YPAI-managed infrastructure, customer systems or a hybrid. API access and custom integrations are available on a project-specific basis. Third-party tools can be adapters; YPAI's native human review remains platform core.
Start Your Data Pilot
Stop training on studio recordings that fail in real cars. Our automotive-specific voice data includes the dialects, age groups, and noise conditions your competitors are already using.
GDPR-aligned scoping • EEA residency options • One-business-day response
FAQ
YPAI delivers in-cabin speech datasets and annotation pipelines for command-and-control, conversational HMI, and driver-monitoring applications. The deliverable includes consented in-cabin recordings across driver and passenger seats, multi-device captures (OEM mic array, headset, smartphone), command-grammar markup, and intent labelling against the customer-supplied dialog model. Production reference points: BYD and Cerence AI are named YPAI clients.
Collections are run in real cabins with real road noise, infotainment cross-talk, and HVAC profile, not in soundproof studios. Speakers are recruited natively per locale (no synthetic dubbing) and recordings cover driver-only, driver-plus-passenger, and multi-occupant scenarios. Device variety mirrors the deployment hardware so the corpus reflects acoustic conditions the deployed ASR or NLU model will actually encounter.
YPAI delivers provenance bundles, traceability of changes, reviewer-qualification records, and dataset documentation structured for the customer audit trail. GDPR controls, EEA processing terms, Article 10 evidence, and project-specific acceptance criteria are written into the DPA and SOW.
YPAI covers tier-1 European and Nordic languages (English-US/UK, German, French, Italian, Spanish, Dutch, Polish, Norwegian, Swedish, Danish, Finnish), major Asian languages (Mandarin, Cantonese, Japanese, Korean), and a growing set of Middle Eastern and Latin American locales. Code-switched speech (common in EU drivers) is annotated rather than collapsed to a single dominant language.
Yes. Custom wake-word datasets (positive examples, hard-negative confusables, accent variety, far-field acoustics) and barge-in test corpora (speaker interrupting active prompt playback) are delivered as scoped engagements. The dataset is paired with an evaluation harness so the customer can measure false-accept and false-reject rates against a documented baseline.
Yes. Voice data is biometric and special-category under GDPR Article 9, so collections run on explicit consent with identity-of-controller disclosure and an Article 35 DPIA. Recordings stay inside EU residency unless the engagement explicitly authorises a non-EU region. The data-handling stance is documented in the DPA shipped with the SOW.
The pipeline is built around the customer deployment environment and the EU AI Act data-governance evidence required for safety-relevant in-cabin systems. Device variety, acoustic profile, and multi-occupant scenarios are documented against deployment reality rather than a clean-studio benchmark. See automotive solutions for the full engagement model.
