---
title: "Audio and Speech Data Annotation for Production AI | YPAI"
url: https://ypai.ai/annotation/audio-speech-annotation-services/
description: "YPAI annotates existing audio for ASR, voice, and speech-LLM teams: transcription, diarisation, events, emotion, intent. EEA processing by default."
source: "src/copy/routes (route /annotation/audio-speech-annotation-services/)"
---
# Audio and Speech Data Annotation for Production AI
> YPAI annotates existing audio for ASR, voice, and speech-LLM teams: transcription, diarisation, events, emotion, intent. EEA processing by default.
## Schema lock
- Label set, taxonomy, and edge-case policy fixed with your team before anyone annotates. Verbatim-versus-clean, disfluency handling, and overlap conventions are decided here, where they are cheap to change.
## Versioned guideline
- Task definitions, segmentation rules, and ambiguity handling written down and version-controlled. The guideline is versioned and forms part of your EU AI Act Article 10 provenance record.
## Calibration round
- A pilot batch on a shared subset, labelled blind by multiple annotators. We measure inter-annotator agreement and timestamp tolerance, then refine the guideline where annotators disagreed.
## Agreement gate
- Production starts once the calibration round clears the kappa and timestamp tolerance agreed for your tasks. Targets are kappa at or above 0.8 for objective labels, 0.6 to 0.75 for subjective ones.
## Production with adjudication
- Annotation runs on self-hosted CVAT and Label Studio inside EEA infrastructure. Gold items are seeded throughout, and every annotator disagreement escalates to senior adjudication.
## QA and delivery
- Human QA is applied according to the agreed acceptance and sampling plan. The per-task agreement report, GDPR Article 30 processing records, signed DPA, and sub-processor list ship with the labels.
## Is voice data automatically special-category under GDPR Article 9?
No. Voice becomes Article 9 biometric special-category only when it is processed to uniquely identify a person, such as voiceprint or speaker-identification tasks. Transcription, diarisation, alignment, and event labelling run under a GDPR Article 6 basis with Article 7 consent. We assign every task its lawful basis before work begins and document it for your DPO, so the Article 9 obligations attach only where they actually apply.
## Can annotation run inside our own infrastructure?
Yes. We can run annotation inside your own EEA infrastructure or a controlled environment, so the audio stays inside your boundary. You get a vetted multilingual workforce, kappa-gated QA and senior adjudication, already built and calibrated.
## Where is our audio processed?
Inside the EEA by default, from intake to erasure. YPAI is a Norwegian company; EEA-only sourcing is available on request, with data residency, subprocessors and transfer controls defined per project. Erasure runs on a 30-day GDPR Article 17 SLA, and the member-state processing region is negotiable per engagement.
## What output formats do you deliver?
Your schema first: client-schema JSON for whatever your pipeline ingests, plus the standards your tooling already expects, RTTM for diarisation, TextGrid for aligned transcripts and prosody, CTM for word and phone timestamps, and CSV for events. Compatible with self-hosted CVAT and Label Studio. The labels are your work product, owned by you.
## Is this human annotation or auto-labelling?
Human annotation, with QA applied according to the agreed acceptance and sampling plan. Models assist the annotators, and the deliverable is expert human judgement.
## What audio and speech annotation tasks does YPAI support?
YPAI delivers verbatim and clean transcription, speaker diarisation, named-entity tagging on transcripts, intent and sentiment labelling, prosody and emotion markup, language identification, code-switching segmentation, and clinical speech annotation. Domain-specific overlays (automotive command grammars, clinical vocabularies, financial entities) are added on top of the base transcription layer rather than re-running annotation from scratch.
## Which languages does YPAI cover for speech annotation?
YPAI annotates speech in 150+ languages and dialects, with native-speaker reviewers concentrated in European and Nordic markets and significant coverage of major Asian, Middle Eastern, and Latin American languages. Code-switched and dialect-heavy speech (Norwegian dialects, Arabic dialect continuum, Swiss German) is handled by reviewers recruited from the relevant region.
## Does YPAI annotate noisy or in-cabin audio?
Yes. In-cabin automotive speech (multi-occupant, road noise, infotainment cross-talk), industrial floor recordings, contact-centre audio with line-noise, and clinical exam-room conversations are recurring formats. Annotators are calibrated against the actual acoustic profile of the deployment. See automotive voice recognition for the in-cabin speciality.
## What transcription accuracy does YPAI target?
Word-error-rate targets are set per engagement against the acoustic profile and domain vocabulary. Clean read speech in tier-1 languages targets sub-2% WER on the audited sample; noisy in-cabin or clinical speech is scoped to a realistic ceiling based on the input quality. Acceptance criteria are written into the SOW and measured on a held-out QA slice.
## Is speech annotation GDPR-compliant?
Yes. Voice is biometric and special-category data under GDPR Article 9, so YPAI runs explicit-consent flows, lawful-basis documentation, and Article 35 DPIA scaffolding. Voice prints are not re-used across engagements and recordings stay inside EU residency. Subject-rights requests resolve via the data request form. The data-handling stance for clinical voice is documented under ethical framework.
## Can YPAI deliver speech corpora suitable for EU AI Act Article 10?
Yes. The provenance bundle (collection date, locale, recruiter pool, consent identifier, device class, post-processing) is structured for Article 10 dataset governance. Bias documentation, representativeness analysis, and the data-cleaning record are part of the deliverable. The bundle slots into the customer Technical File.
## Does YPAI work with customer-supplied audio or only collected audio?
Both. Customer-supplied recordings are accepted under a DPA that documents the lawful basis and consent chain. Annotation proceeds once the provenance check is complete. Net-new collections are common when the customer corpus does not match production acoustic conditions. The collection arm at /data-collection/ handles the recording side.