Voice evaluation · Accent Adaptation
AI Voice Evaluation for Accent Adaptation
Human evaluation of your speech models: MOS and preference testing for TTS, WER-in-context review for ASR, and native-speaker judgement on naturalness and intelligibility. Applied to accent adaptation, the specification is driven by one thing: per-accent wer spread.
- Service
- Voice evaluation
- Use case
- Accent Adaptation
- Primary metric
- Per-accent WER spread
Required data profile
- Accent-band balanced speech with substrate-language tags
- Matched content across bands for controlled comparison
Technical specification
| Parameter | Standard |
|---|---|
| TTS | MOS (1-5), MUSHRA, and A/B preference protocols |
| ASR | Error typing: substitution, deletion, insertion, code-switch failure |
| Panel | Native speakers of the target variety, screened and calibrated |
| Sample size | Powered per the effect size you need to detect |
| Reporting | Per-item scores plus aggregate with confidence intervals |
Process
- Protocol design and sample-size calculation
- Panel recruitment and calibration on reference items
- Blind evaluation with attention checks
- Statistical analysis
- Report with per-error-type breakdown
Metrics this feeds
- Per-accent WER spread
- Regression on the original accent set
Failure modes to design out
- Treating Indian English as one accent
- No substrate tagging, so the model cannot be evaluated per band
Attention checks and reference anchors are embedded so unreliable raters are detected and excluded before analysis.
Deliverables
- Raw per-rater scores
- Aggregated results with confidence intervals
- Error-type analysis
- Recommended fix priorities
Frequently asked
Is voice evaluation the right service for accent adaptation?
It covers accent-band balanced speech with substrate-language tags. Most accent adaptation 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 evaluation for accent adaptation
Send the metric you need to move.