Voice evaluation · LLM Evaluation
AI Voice Evaluation for LLM Evaluation
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 llm evaluation, the specification is driven by one thing: rubric scores with confidence intervals.
- Service
- Voice evaluation
- Use case
- LLM Evaluation
- Primary metric
- Rubric scores with confidence intervals
Required data profile
- Native-speaker rater panels per language
- Rubric-based scoring with calibration
- Overlapping assignments for agreement
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
- Rubric scores with confidence intervals
- Inter-rater agreement
- Failure-mode distribution
Failure modes to design out
- Raters who are fluent but not native in the variety
- Rubrics written in English and applied to non-English output without localisation
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 llm evaluation?
It covers native-speaker rater panels per language. Most llm evaluation 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 llm evaluation
Send the metric you need to move.