Data for speech AI

Recognition models are only as good as the voices, devices and rooms they heard in training.

What Speech AI needs

Speech models fail quietly on accents, ages and rooms that were missing from training. The fix is recruiting against those gaps on purpose.

We collect and transcribe speech to your quotas: language, dialect, age band, gender, region, device and acoustic environment, each recorded in the file's metadata so you can audit the mix.

Data types

Speech
Audio
Transcripts

Industries

Telecom
Automotive
Banking and finance
Healthcare
Consumer devices
Media and entertainment

The data it takes

Conversational speech
Two-person or group conversations on set topics, recorded on mobile or landline.
Scripted reads
Prompted sentences and numbers for clean coverage of words and sounds.
Wake words and commands
Short utterances at varied distances, angles and noise levels.
Call-centre audio
Agent and customer speech with channels separated and personal data redacted.
Transcripts and timestamps
Verbatim or clean transcription with speakers and time codes.

How we collect it

01
Quota-based recruitment
Speakers sourced against your language, dialect, age and gender targets.
02
Real devices and rooms
Recording on the phones and microphones your users have, in homes, offices, streets and vehicles.
03
Checked on capture
Clipping, silence and noise are caught in the recorder before upload.
04
Transcribed by native speakers
Machine pre-fill corrected by transcribers, then sample-reviewed with a word-error gate.