---
license: mit
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
- config_name: finetune
  data_files:
  - split: train
    path: finetune/train-*
  - split: validation
    path: finetune/validation-*
  - split: test
    path: finetune/test-*
dataset_info:
- config_name: default
  features:
  - name: file
    dtype: string
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: text
    dtype: string
  - name: duration
    dtype: float32
  - name: student_id
    dtype: string
  - name: date
    dtype: string
  - name: time
    dtype: string
  - name: module
    dtype: string
  - name: investigation
    dtype: string
  - name: part
    dtype: string
  splits:
  - name: train
    num_bytes: 43732745924.625
    num_examples: 181323
  - name: validation
    num_bytes: 5529107838.5
    num_examples: 23652
  - name: test
    num_bytes: 5385316354.0
    num_examples: 22592
  download_size: 50216196525
  dataset_size: 54647170117.125
- config_name: finetune
  features:
  - name: file
    dtype: string
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: text
    dtype: string
  - name: duration
    dtype: float32
  splits:
  - name: train
    num_bytes: 12603945060.375
    num_examples: 51029
  - name: validation
    num_bytes: 2082115799.625
    num_examples: 8459
  - name: test
    num_bytes: 2224927204.0
    num_examples: 9200
  download_size: 16055315812
  dataset_size: 16910988064.0
---

NOTE: This is not a public dataset, I couldn't share access.

There are two config for this dataset:
 1. By default, is loading the raw dataset with basically everything of the dataset
 
 2. There is another configuration is for finetune use, which is a preprocessed myst subset with
    - cleaned transcription (in the format w2v2 output)
    - duration, only 2~20 sec audio entries will be seen in this subset
    - *local file name: only for reference use locally.

```python
  from datasets import load_dataset

  myst = load_dataset("MagicLuke/MyST", split="test")
  myst = load_dataset("MagicLuke/MyST", "finetune", split="test")
```