Voice recording · Speech Emotion Recognition
Voice Recording for AI Training for Speech Emotion Recognition
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 emotion recognition, the specification is driven by one thing: per-class f1.
- Service
- Voice recording
- Use case
- Speech Emotion Recognition
- Primary metric
- Per-class F1
Required data profile
- Elicited and natural emotional speech
- Multi-rater emotion labels with adjudication
- Balanced across emotion classes
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
- Per-class F1
- Inter-rater agreement on labels
- Escalation detection latency
Failure modes to design out
- Acted emotion only
- Single-rater labels on an inherently subjective task
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 emotion recognition?
It covers elicited and natural emotional speech. Most speech emotion recognition 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 emotion recognition
Send the metric you need to move.