GitHub / Ibraddah / SHL-Grammar-Scoring-Engine-for-Voice-Samples
This model predicts grammar scores (1–5) from audio files. It uses Whisper to transcribe speech to text, cleans the text, and extracts features with TF-IDF. A Random Forest Regressor is trained to learn grammar score patterns. Evaluation via Pearson Correlation showed good results.
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PURL: pkg:github/Ibraddah/SHL-Grammar-Scoring-Engine-for-Voice-Samples
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Forks: 0
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License: None
Language: Jupyter Notebook
Size: 34.2 KB
Dependencies parsed at: Pending
Created at: 4 months ago
Updated at: 4 months ago
Pushed at: 4 months ago
Last synced at: 4 months ago
Topics: audio-to-text, grammar-scoring, machine-learning, model-evaluation, pearson-correlation, random-forest, regression-model, speech-recognition, submission-pipeline, text-preprocessing, tf-idf, whisper-model