aigc-x/Pronunciation-boldvoice
Pronunciation Assessment Dataset (BoldVoice + speechocean762) Dataset for fine-tuning multimodal models on English pronunciation assessment. Overview Source Samples Audio Duration Description BoldVoice 38,182 10-20s Non-native English learners, BoldVoice API annotations speechocean762 5,000 1.6-20s Public dataset, 5-expert scored, Mandarin speakers Total 43,182 Schema Column Type Description audio Audio (16kHz mono)… See the full description on the dataset page: https://huggingface.co/datasets/aigc-x/Pronunciation-boldvoice.
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Pronunciation Assessment Dataset (BoldVoice + speechocean762)
Dataset for fine-tuning multimodal models on English pronunciation assessment.
Overview
Schema
Annotation Format (response JSON)
{
"words": [
{
"word": "bear",
"expected": ["B", "EH", "R"],
"actual": ["B", "AH", "R"],
"is_correct": false,
"errors": [{"index": 1, "expected": "EH", "actual": "AH", "type": "substitution"}]
}
],
"summary": {
"total_phonemes": 3,
"correct_phonemes": 2,
"error_count": 1,
"score": 67
}
}- Phonemes in ARPAbet notation (no stress markers)
- Error types:
substitution,deletion,insertion,mispronounced
Fine-tuning
pip install -r requirements.txt
# Fine-tune Gemma 4 E2B-it with LoRA
python finetune_gemma4_e2b.py --model google/gemma-4-E2B-it
# Custom settings
python finetune_gemma4_e2b.py --model /path/to/local/model --lr 1e-4 --epochs 2 --batch-size 2