Spoken Grammar Scoring Engine
A multimodal machine learning model for scoring spoken English grammar on a continuous 0–5 scale.
The model combines:
- Acoustic speech features
- Whisper-based speech transcription
- Linguistic features from the transcript
- MiniLM semantic embeddings
- Ensemble regression
Performance
- 5-Fold CV RMSE: 0.6876
- 5-Fold CV Pearson: 0.8338
- Kaggle Public Score: 0.5278
The model was developed for the SHL Hiring Assessment 2026 and is an independent implementation for spoken grammar assessment.
Author: Satyam Kumar
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support