QAEF is QariAI's implementation of an open, standardized methodology for evaluating AI Quranic recitation systems โ the first of its kind.
Technical specification on GitHub โDefinition: Quranic recitation evaluation is the measurement of phonetic accuracy, rule compliance, temporal precision, feedback quality, and robustness across speakers.
QAEF analyzes recitation at the phoneme level, identifying errors in articulation points (makharij) and phonetic characteristics (sifaat).
The system detects application of Tajweed rules in real time and classifies errors by rule type, enabling precise correction.
QAEF evaluates temporal aspects of recitation to ensure alignment with proper recitation structure.
QAEF generates structured feedback designed to be pedagogically actionable โ not just flagging errors, but guiding correction.
The system is designed to perform consistently regardless of speaker background.
| Dimension | Traditional Learning | QAEF |
|---|---|---|
| Feedback latency | Delayed | Immediate |
| Practice frequency | Limited | Unlimited |
| Consistency | Variable | Standardized |
| Error specificity | Instructor-dependent | Rule-based |
QAEF complements traditional learning โ it enables high-frequency structured practice, not a replacement for scholarship.
QAEF is a support system, not a replacement for human scholarship.
Built on the Open Evaluation Methodology
QAEF operationalizes the principles defined in QariAI's open methodology. Both documents are publicly licensed (CC BY 4.0) to enable transparent, reproducible benchmarking.
QariAI applies QAEF to your recitation in real time โ identify your weak rules and improve systematically.
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