Voice recording · Speech Analytics
Voice Recording for AI Training for Speech Analytics
Studio voice recording built for model training rather than broadcast: controlled acoustics, consistent mic distance, and reproducible session parameters across every speaker. Applied to speech analytics, the specification is driven by one thing: intent accuracy.
- Service
- Voice recording
- Use case
- Speech Analytics
- Primary metric
- Intent accuracy
Required data profile
- Domain-realistic conversation audio
- Intent, outcome and compliance labels
- Speaker-separated channels
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
- Intent accuracy
- Compliance-event recall
- Summary factuality
Failure modes to design out
- Labels defined without listening to real calls first
- Ignoring dialect coverage in the target market
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 speech analytics?
It covers domain-realistic conversation audio. Most speech analytics 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 speech analytics
Send the metric you need to move.