SPEECH DATA FOR ASR, TTS AND VOICE AI. BUILT IN THE EEA

Same test, Norwegian training. 36% lower WER out of domain.

Speech models fail where their training data never went. Dialect, spontaneous speech, code-switching.

NB-Whisper large 6.6% vs OpenAI Whisper large-v3 10.4% · FLEURS Bokmål · Kummervold et al., Interspeech 2024

Scope a speech data requirement Read the technical specification →

Condition

Drag across the image to move through the recording

RECORDING CONDITIONS Device · Setting · Speakers · Speech type

Four axes decide whether your speech data survives deployment

You name the range your system has to hold. The corpus is built to span it, and every recording lands with its coverage recorded.

AXIS 01

Device

The microphone in the user's hand, not the one in the studio. A model trained on one tier degrades on the next.

  • Smartphone tier
  • USB headset
  • In-vehicle microphone
  • Lavalier and body-worn
  • Far-field array
  • Studio condenser

AXIS 02

Setting

The room, the vehicle, the street. Noise, reverberation and competing speech are specified, not hoped for.

  • Studio
  • Home
  • Contact centre
  • Automotive cabin
  • Clinic and ward
  • Street and outdoor

AXIS 03

Speakers

Recruited by dialect region, age and background, so the long tail is represented rather than averaged away.

  • Dialect region
  • Age range
  • Gender identity
  • Second-language accent
  • 150+ languages, Nordic and low-resource depth

AXIS 04

Speech type

Targeted capture of the speech a benchmark removes and production does not.

  • Read and prompted
  • Spontaneous
  • Multi-speaker and overlapping
  • Code-switched mid-sentence
  • Wake word and command
  • Emotional and expressive

Coverage is agreed before recording begins and delivered with the dataset. Where a required range cannot be covered, YPAI says so during scoping.

COVERAGE, RECORDED Device × Setting · 36 conditions

A benchmark covers one corner. A corpus covers the grid

Every cell is a named condition, device by setting. Public benchmarks cluster in the quiet corner: read speech, one microphone, one dialect. Your corpus is specified against the cells your users speak in, and the coverage ships with the data.

YOUR VOICE, CLEAN AND WITH NOISE Quiet recording · With noise mixed in

Hear it on your own voice

Record three seconds somewhere quiet. The same recording is transcribed clean, then again with contact-centre, cabin or street noise mixed in at a level you choose. The words that change are what training data has to cover.

Quiet recording reference

start route guidance to the harbour terminal

With noise mixed in Street · traffic

stop root guidance to harbour tunnel

Runs in this tab, on your device Example shown until you run it. Illustrative, no customer data

WHICH SITUATION ARE YOU IN Collection · Voice · Labels · Evaluation · Licensing · Specification

Choose the work that matches the gap

Six routes into the same work. Each names what it produces and where its depth lives, and every route delivers consent, metadata and a QA trail per recording.

  1. The speech you need does not exist yet

    YPAI designs the collection, recruits and qualifies the speakers, and runs the recording operation. Read, prompted, spontaneous, conversational, command or wake-word speech, remote or in studio, delivered against agreed speakers, conditions and checks.

    Coverage and recruitment

  2. One voice matters more than population coverage

    Specialist voice recording defines casting, pronunciation, performance and recording conditions. Recorded voice files with model-use rights stated in writing; voice-cloning, buyout, exclusivity and resale rights need an explicit written grant.

    Voice recording and rights

  3. You have audio, but the model cannot use it

    Labelled corpora pair source audio with an agreed schema and review standard: transcription, segmentation, diarisation, alignment and linguistic annotation, checked by native reviewers with the QA trail kept.

    Transcription, diarisation and labels

  4. Locate the failure before adding data

    Evaluation packages pair a set, rubric and reviewer process, then separate results by language, dialect, device, setting or speaker group. The output can include an error taxonomy and a regression set your team can run again.

    Evaluation sets and regression

  5. Could an existing dataset fit?

    YPAI reviews an existing or partner-sourced dataset against intended use, speech type, acoustic conditions, format, provenance and permitted rights. Item-specific licence, gap-fill scope, or both.

    Dataset review and licensing

  6. Your receiving team needs a definition of correct delivery

    A technical specification for the receiving system: formats, channel and track structure, transcript schema, metadata, validation and the conditions for acceptance.

    Technical specification

Specialist collection, 15 areas Explore collection

  1. Nordic and low-resource languages
  2. Dialect and accent corpora
  3. Conversational and multi-speaker audio
  4. Full-duplex dialogue for voice agents
  5. Code-switching speech
  6. In-car and automotive voice
  7. Contact-centre dialogue
  8. Clinical and healthcare speech
  9. Wake words and voice commands
  10. Far-field and noisy environments
  11. TTS voice production
  12. Emotional and expressive speech
  13. Studio, field and in-person capture
  14. Parallel corpora and MTPE, 300+ language pairs
  15. Ready-made speech datasets

A speech type or setting not listed here? YPAI designs the capture protocol around the deployment; describe the system and the condition it runs under.

Scope a corpus

HOW A CORPUS IS BUILT Coverage specification · Capture · Quality gates · Delivery

Every recording arrives with its consent, metadata and QA trail

Four stages. Each adds to the metadata that travels with the audio, so every delivery arrives ready to inspect.

One recording. Lavalier and body-worn · Street and outdoor · Spontaneous

  1. Coverage specification

    The four axes are turned into quotas: which dialects, which settings, which devices, and how much of the edge. Pool depth per language and accent is stated before signature.

    • Quotas Held within 5 percentage points per cell
    • Acceptance Criteria written before recording starts

  2. Capture

    Identity-checked speakers record under the specified conditions, with consent per recording.

    • Studio 48 kHz / 24-bit, SNR 40 dB or better
    • Field 16 kHz or above, SNR and environment class per file

  3. Quality gates

    Automated technical QC on every file, then native-reviewer transcription checks against the agreed sampling plan.

    • Floor 98% first-delivery acceptance, re-collected below it
    • Evaluation WER reported per dialect group

  4. Delivery

    Audio, transcripts and metadata in the formats and location you named, with a signed manifest.

    • Pilot Output within 10 business days of kick-off
    • Destination S3, GCS, Azure, SFTP or on-premise

Formats, channel and track structure, transcript schema, validation and acceptance are described in full. Read the technical specification →

WHO SPEAKS Recruited · Identity-checked · Qualified · Calibrated · Reviewed

Qualified speakers, not a crowd

Every speaker is recruited, identity-checked and qualified for the specific corpus they record in, by dialect region where the corpus needs it.

  1. Recruited

    Sourced for the corpus's languages, dialect regions, demographics and settings

  2. Identity-checked

    Identity on file, consent per recording

  3. Qualified

    Passes the corpus's own screening recordings before production

  4. Calibrated

    Transcript agreement tracked per dialect group during production

  5. Reviewed

    Independent native-linguist review on sampled work

Corpora draw on a network of 210,000+ registered contributors across 50+ countries; each corpus uses only the contributors qualified for it.

CONSENT, RIGHTS AND RESIDENCY Legal basis · Consent · Rights · Provenance · Residency · Agreements

The consent, rights and residency answers your legal and security review asks for

A recording can meet its technical requirements while its permission does not cover the next intended use. Rights, evidence and delivery stay connected, produced as the work runs.

Where a person is in the recording, consent travels with the file.

What the review asks, and the answer

  1. 01 What is the legal basis for each recording?

    Legal basis Consent, per person, per purpose and per session, documented per recording

  2. 02 Can you show consent, per speaker, and what happens on withdrawal?

    Consent GDPR Article 7, collected on the YPAI platform; withdrawals quarantined within 72 hours, reported within one business day, erased within 30 days

  3. 03 Which uses does the release cover?

    Rights Evaluation, model-training and commercial-deployment permissions defined separately; voice-cloning and resale only by explicit written grant

  4. 04 Where did each recording come from?

    Provenance Consent record, capture metadata and SHA-256 hash per file; Croissant 1.1 description and a data card in EU AI Act Article 10 order per dataset

  5. 05 Where does the audio reside, and under whose jurisdiction?

    Residency EEA by default, Norwegian jurisdiction; EEA-only sourcing and processing on request

  6. 06 What governs the engagement on paper?

    Agreements DPA signed, SCCs available for cross-border transfer

What the platform records for every delivery

Controls
Delivery controls How this maps to AI Act risk classes
YPAI Platform
YPAI Data Collection & Assurance Platform What one recording carries
  1. capture consent recorded · 48 kHz · 24-bit · far-field YPAI's own audio collection platform, with consent recorded per contributor
  2. labelling transcript and speaker turns checked against the guideline Native human-review console as the platform core
  3. inspection sampled lot · coverage gap · 3 recordings re-collected Self-hosted European annotation servers
  4. evaluation WER reported per dialect group Credentialed domain reviewers where the work requires them
  5. delivery manifest · integrity check · erasure within 30 days Residency, subprocessors and transfers defined per engagement

Every delivery carries the records the engagement requires and an integrity check on what is delivered.

WHERE THE SPEECH HAPPENS Healthcare · Automotive · AI and model companies · Public sector · Industrial and energy · Education

The vocabulary, the room and the rules change with the industry

A clinic, a cabin and a contact centre do not sound alike, and the consent, residency and acceptance rules differ as much as the acoustics. Six industries carry their own speech pages; every other one starts at the intake below.

All industry solutions →

  1. Healthcare

    Clinical speech for ambient documentation and dictation in Nordic languages, recorded under consent frameworks a hospital review can read.

    EEA processing by default, consent per recording

    Healthcare

  2. Automotive

    In-cabin voice across dialects, road noise and microphone positions, for wake words, commands and multilingual driver interaction.

    Cabin, city and motorway conditions

    Automotive

  3. AI and model companies

    Training and evaluation corpora for ASR, TTS and speech-to-speech models, with dialect-balanced sets and results separated per condition.

    WER reported per dialect group

    AI and model companies

  4. Public sector

    Citizen-facing speech in Bokmål, Nynorsk and the dialects between them, for service lines, case dictation and accessibility, under Norwegian jurisdiction.

    EEA processing by default, Norwegian jurisdiction

    Public sector

  5. Industrial and energy

    Voice on the floor and in the field, with hearing protection, machinery noise, radio and far-field capture for inspection and maintenance workflows.

    Far-field and noisy-environment capture

    Industrial and energy

  6. Education

    Learner speech across ages and accents, pronunciation and reading data for language learning and accessibility products.

    Nordic and European language breadth

    Education

PILOT TO PRODUCTION Collection · Annotation · Validation · Human and model evaluation · Accepted

One pilot against your requirement.

A pilot is scoped to your specification, quality thresholds and acceptance criteria, and reviewed against them before anything scales. Scope and commercial terms are agreed before it starts. Production is a separate decision, taken after the pilot review.

The pilot fixes

  • Scope of work
  • Technical requirements
  • Acceptance criteria
  • Data protection and rights
  • Commercial structure
  • Remediation and change control
  1. scope your specification and acceptance criteria
  2. terms scope and commercial terms agreed before it starts
  3. review against the agreed criteria, in a pilot workspace
  4. production a separate decision, taken after the review

Production: a separate decision, taken after the pilot review

Scope a pilot

ENGAGEMENT PROCESS

From the first brief to a production corpus

  1. 01 Describe the system What it has to do, where it fails, and how the resulting data will be used.
  2. 02 Feasibility read Languages, dialects, settings and volume checked against pool depth before anything is promised.
  3. 03 Pilot delivery Representative output within 10 business days to validate quality gates, formats and the record.
  4. 04 Production corpus Weekly deliveries with per-dialect QA, versioning and the signed manifest.

GDPR Article 7 · EU AI Act Article 10 · DPA included

The brief

Looking for work on AI projects? This form is for companies. Apply as a freelancer

Speech type (optional)

Include: languages and dialects, settings and devices, speech type, volume estimate, and any rights or residency constraints.

GOVERNANCE

Consent, rights and audit readiness

What governance artefacts can be delivered with a speech dataset?

Consent records per speaker, capture metadata and a SHA-256 hash per file, demographic and dialect breakdowns, QA audit trails, a Croissant 1.1 description and a data card written in the order EU AI Act Article 10 asks for, and a signed data processing agreement.

Can the same recordings be used for training, evaluation and a commercial product?

Only if the release says so. YPAI defines evaluation, model-training and commercial-deployment permissions separately, with territory, term, withdrawal handling, deletion and retention. If the recordings will feed models you have not named yet, that use is written in rather than assumed later.

What happens when a speaker withdraws consent?

The recordings are quarantined in YPAI systems within 72 hours, the withdrawal is reported to you within one business day with a ledger entry, and erasure completes within 30 days.

Where is the audio processed and stored?

Primary operations are in Norway on EEA infrastructure. Projects can be structured for EEA-only participant sourcing and processing; US or on-premise delivery is arranged where a deployment requires it.

How is transcription quality measured on dialectal speech?

Transcripts are checked by native linguists for the dialect region, agreement is measured per dialect group rather than as one blended average, and disagreements are adjudicated by a dialect-specialist reviewer before the corpus is used for training or evaluation.

Bring the system, the corpus or the performance gap.

If YPAI is not the right fit, we will say so directly.

Scope a speech data requirement Read the technical specification →