README.md

metadata

license: apache-2.0
task_categories:
  - audio-classification
language:
  - en
size_categories:
  - 10K<n<100K
tags:
  - pronunciation-assessment
  - phoneme
  - speech
dataset_info:
  features:
    - name: audio
      dtype:
        audio:
          sampling_rate: 16000
    - name: reference_text
      dtype: string
    - name: response
      dtype: string
    - name: source
      dtype: string
    - name: duration
      dtype: float64
    - name: score
      dtype: int64
  splits:
    - name: train
      num_bytes: 36605701980
      num_examples: 43182
  download_size: 36476677163
  dataset_size: 36605701980
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

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)	Speech recording
reference_text	string	Text the speaker intended to read
response	string	JSON annotation (see below)
source	string	boldvoice or speechocean762
duration	float	Audio duration in seconds
score	int	Overall pronunciation score (0-100)

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

Token Budget

Metric	Value
Median tokens/sample	1,197
p95 tokens/sample	2,674
Max tokens/sample	6,143