Use cases

Speech data scoped to your model and deployment.

From regional in-car speech to multi-speaker transcription, we scope collection, annotation, and evaluation data around your language, environment, format, rights, and acceptance criteria. Feasibility, volume, schedule, and delivery are confirmed in a written project brief.

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Where we fit

Voice AI needs speech data matched to its deployment conditions.

In-car systems, call centers, assistants, and healthcare devices can fail in different ways. A useful project brief defines the speakers, acoustic conditions, labels, and evaluation slices the model is expected to handle.

Going deeper on a use case? See our guides on ASR training data, TTS training data, in-car voice data, and multilingual speech data.

01 · Cabin scenario

Illustrative scenario only. Languages, conditions, speakers, transcripts, values, and status labels are not customer records, live availability, or promised results.

In-car voice across regions, accents, and noise.

Wake word DA · SV · NO · DE HVAC on 60 km/h
Driver: "Hej bil, kør hjem."
Passenger: "Sätt på musiken."
Cabin noise condition + accent metadata captured per take.
02 · STT transcript

Illustrative scenario only. Languages, conditions, speakers, transcripts, values, and status labels are not customer records, live availability, or promised results.

Word-level timestamps, low-confidence flags, dialect coverage.

Domain audio Word timestamps Agreement metric Eval split defined
[00:01.420 → 00:01.890] "patient" · spk_02 · conf 0.97
[00:01.910 → 00:02.310] "tachycardia" · spk_02 · conf 0.62 ⚑
Low-resource accents structured into a controlled eval set.
03 · TTS session

Illustrative scenario only. Languages, conditions, speakers, transcripts, values, and status labels are not customer records, live availability, or promised results.

Studio-grade capture with linked speaker metadata.

48 kHz / 32-bit Expressive prompts Voice profile linked Take 03 ✓
Script line 04 of 120 · neutral → warm → urgent passes.
Speaker: F · 32 · DK central · trained voice talent.
Room, microphone, and placement controls documented per session.
04 · Conversation & assistive

Illustrative scenario only. Languages, conditions, speakers, transcripts, values, and status labels are not customer records, live availability, or promised results.

Multi-speaker dialogue and accessibility-first capture.

Multi-speaker Channel-separated Consent scope Channel plan
Agent (ch L): "Let's pull up your account first."
Customer (ch R): "It's been three calls about this."
Speaker selection and consent designed around accessibility.
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In-car voice-data requirements

An automotive brief can define cabin noise, regional accents, vehicle state, devices, and overlapping passenger speech as collection or evaluation variables.

Example conditions for a European in-car brief; locale and road feasibility are confirmed per project.

Speech data scoped for STT training and evaluation

A project can define multilingual STT training or evaluation data around specified speech variation, overlapping speakers, and noisy recording conditions.

Coverage targets can include regional and lower-resource dialects when recruitment and review feasibility are confirmed.

Scope TTS data for emotional delivery, multilingual recordings, and long-form sessions

TTS collection benefits from stable acoustic conditions because changes in room, microphone, or speaker position can become part of the learned voice. We scope the recording environment, prompt styles, retakes, session controls, and acceptance checks in writing for each project.

Recording controls and acceptance criteria agreed before capture.

Conversation data for varied caller behavior

Polished audio scripts do not represent customer-support calls where people interrupt or speak over each other. A conversational collection can be scoped around separate channels, overlap, scenario design, transcript conventions, and routing labels.

Customer support, call routing, accessibility research, and assistive devices.

How we tailor it

Three variables to define in a use-case brief.

Accent & dialect coverage

Vetting Speakers by Region, Not Language Codes.

Speaker targets can be grouped by regional dialect, age range, gender profile, and other approved criteria. The recruitment method, metadata fields, and consent requirements are confirmed in the project scope.

Recording environment

Choose a Capture Method for the Conditions That Matter.

Remote, moderated, on-site, or customer-provided capture can be assessed against the target acoustic profile. Recording location, equipment, staffing, and feasibility are confirmed before commitment.

Evaluation sets

Design Held-Out Sets Around the Failures That Matter.

Train, development, and test separation can be scoped with slices for background noise, regional accents, and dialogue difficulty. The split method, labels, metrics, and acceptance thresholds are agreed with the buyer.

How we run it

Same workflow, configured per use case.

Three steps from a data brief to an agreed collection, delivery, and acceptance plan.

01 · Map

Mapping out target variables before recording.

We document speaker profiles, acoustic constraints, audio formats, rights, and acceptance criteria so the collection is designed around the intended deployment environment.

02 · Collect

Gathering natural audio through the right channel.

We assess remote, moderated, on-site, or customer-site capture against the target conditions. The quote identifies location, equipment, staffing, security, and feasibility instead of assuming one collection method fits every brief.

03 · Deliver

Delivery and acceptance checks defined in the brief.

Audio, labels, metadata, and QA records are reviewed against the agreed acceptance criteria. The file formats and audit artifacts included in delivery are listed in the project scope before collection starts.

Collection offers

Move from a use case to a collection brief.

Choose the closest production scenario to review its capture conditions, annotations, rights approach, sample process, and fit criteria.

Voice agent evaluation data

Private held-out test sets scoped to your callers, channels, languages, accents, noise conditions, and failure modes, with human-reviewed references and documented holdout rules.

Review evaluation requirements

Call-center speech data

Purpose-recorded, consented customer-service simulations with telephony delivery, separate-channel options, human-reviewed transcripts, and custom domain scenarios.

Review call-data requirements

Full-duplex conversational speech data

Separate-channel conversations that preserve natural overlap, interruptions, backchannels, repairs, and turn timing for speech-to-speech and low-latency voice systems.

Review conversation requirements

Audiovisual speech data collection

Synchronized audio and video for visual speech, lip alignment, audiovisual agents, and digital-human research, with the intended model use stated in participant releases.

Review audiovisual requirements

Warehouse voice data collection

Short commands, numbers, item codes, confirmations, and corrections recorded for the headsets, languages, and operating noise used on the floor.

Review industrial requirements

Simulated emergency-call speech data

Consented simulations—not real victim calls—covering multilingual scenarios, urgency, interruptions, degraded phone audio, and human-reviewed reference transcripts.

Review simulated-call requirements

Emotion annotation

Per-turn emotion labels on speech: discrete classes, optional valence and arousal ratings, intent kept separate, and per-class annotator agreement reported.

Review emotion labeling requirements

Call-center emotion annotation

Turn-level emotion and sentiment labels on call audio for quality monitoring, escalation prediction, and agent assist, with a documented consent chain.

Review call-center emotion requirements

Voice agent emotion data

Turn-level affect labels on spontaneous conversational speech, so a voice agent can detect frustration and be evaluated on how it responds.

Review voice agent emotion requirements

TTS evaluation data

Recruited listener panels scoring mean opinion score, naturalness, and emotional appropriateness for expressive speech synthesis, with per-rater agreement.

Review TTS evaluation requirements

Video data collection

Custom video datasets recorded to spec: talking-head and dialogue footage, expression and gesture sets, liveness sequences, and in-cabin captures, with per-participant consent.

Review video collection requirements

Talking-head video data

On-camera monologue and dialogue for avatars, lip sync, and digital humans: fixed framing, frame-accurate sync, and likeness releases that name synthetic-media use.

Review talking-head requirements

Voice anti-spoofing data

Genuine and spoofed speech pairs for deepfake detector training: TTS, voice conversion, and replay attacks generated only from speakers who consented to the spoof.

Review anti-spoofing requirements
Get started

Tell us the speech data you need

Send over your speaker profiles, language needs, and background noise conditions. Our team will assess feasibility and identify what is needed to scope a written project proposal.

Request a quote Review collection configurations
Targeted
contributor recruitment matched to each project brief
Scoped
language and dialect feasibility confirmed per project
Defined
QA workflow and acceptance criteria agreed in scope
Written
rights, artifacts, schedule, and price documented per project