Voice recording · Voice Biometrics
Voice Recording for AI Training for Voice Biometrics
Studio voice recording built for model training rather than broadcast: controlled acoustics, consistent mic distance, and reproducible session parameters across every speaker. Applied to voice biometrics, the specification is driven by one thing: equal error rate.
- Service
- Voice recording
- Use case
- Voice Biometrics
- Primary metric
- Equal error rate
Required data profile
- Many sessions per speaker across days and channels
- Same-speaker channel variation
- Optional spoof and replay sets
Technical specification
| Parameter | Standard |
|---|---|
| Sample rate | 48 kHz |
| Bit depth | 24-bit |
| Microphone | Large-diaphragm condenser, fixed distance, pop filter |
| Room | Treated booth, RT60 under 0.3s |
| Processing | None. No compression, EQ, or noise reduction on delivered audio |
| Session length | 30-90 minutes per speaker, with breaks logged |
Process
- Session template definition so every studio in the network records identically
- Speaker briefing and pronunciation calibration
- Take-level monitoring with immediate re-record on defect
- Per-session technical report
- Delivery with unprocessed masters
Metrics this feeds
- Equal error rate
- Cross-channel EER
- Spoof detection rate
Failure modes to design out
- One session per speaker, which makes intra-speaker variability unmodellable
- No channel variation
Delivered audio is never processed. Training pipelines should see the raw capture so augmentation stays under your control.
Deliverables
- Unprocessed WAV masters
- Session logs
- Take-level metadata
- Speaker consent records
Frequently asked
Is voice recording the right service for voice biometrics?
It covers many sessions per speaker across days and channels. Most voice biometrics programmes combine it with at least one other service; we will say so in the scope rather than selling one line item.
What languages are available?
All 14 languages in the network plus Indian English accent bands.
How is the evaluation set handled?
Collected first, from speakers disjoint from the training cohort, so improvement is measurable.
Scope voice recording for voice biometrics
Send the metric you need to move.