---
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: ipa
    dtype: string
  - name: speaker_code
    dtype: string
  - name: speaker_gender
    dtype: string
  - name: speaker_native_language
    dtype: string
  splits:
  - name: train
    num_bytes: 44466139
    num_examples: 129
  download_size: 44312132
  dataset_size: 44466139
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-nc-4.0
task_categories:
- automatic-speech-recognition
language:
- en
tags:
- Speech
- IPA
- Arabic
- Mandarin
- Spanish
- Hindi
- Vietnamese
- Korean
pretty_name: L2-ARCTIC Suitcase
size_categories:
- 1K<n<10K
---
# L2-ARCTIC Suitcase: a spontaneous non-native English speech corpus
L2-ARCTIC Suitcase Corpus contains English speech from 22 non-native speakers 
of Vietnamese, Korean, Mandarin, Spanish, Hindi, and Arabic backgrounds.
It contains phonemic annotations using the sounds supported by [ARPABet](https://en.wikipedia.org/wiki/ARPABET).
It was compiled by researchers at [Texas A&M University](http://www.tamu.edu/) and [Iowa State University](http://www.iastate.edu/).
Read more on [their official website](https://psi.engr.tamu.edu/l2-arctic-corpus/).

## This Processed Version
We have processed the dataset into an easily consumable [Hugging Face dataset](https://huggingface.co/docs/datasets/en/index) using [this data processing script](https://github.com/KoelLabs/ML/blob/main/scripts/data_loaders/L2ARCTIC.py).
This maps the phoneme annotations to [IPA](https://en.wikipedia.org/wiki/International_Phonetic_Alphabet) as supported by libraries like [ipapy](https://pypi.org/project/ipapy/0.0.1.0/) and [panphon](https://pypi.org/project/panphon/0.5/).
We also correct typos, malformatted annotation files, and split the original 22 samples of varied lengths into 129 samples each between 10 and 12.5 seconds. 
We do this naturally at existing silences in the samples to preserve as much complete semantic meaning of each utterance and make it clear 
which portion of the transcriptions belong to which of the split samples.

**NOTE**: we have a [cleaned version of the full L2-ARCTIC](https://huggingface.co/datasets/KoelLabs/L2Arctic) dataset as well which contains the original 22 samples with just the data cleaning.

- The train set has 129 samples (around 26 minutes of un-scripted speech).

All audio has been converted to float32 in the -1 to 1 range at 16 kHz sampling rate.

## Usage
0. Request access to [this dataset](https://huggingface.co/datasets/KoelLabs/L2ArcticSpontaneousSplit) on the Hugging Face website. You will be automatically approved upon accepting the terms.
1. `pip install datasets`
2. [Login to Hugging Face](https://huggingface.co/docs/huggingface_hub/en/guides/cli#huggingface-cli-login) using `huggingface-cli login` with a token that has gated read access.
3. Use the dataset in your scripts:
```python
from datasets import load_dataset

dataset = load_dataset("KoelLabs/L2ArcticSpontaneousSplit")
spontaneous_ds = dataset['spontaneous']
scripted_ds = dataset['scripted']

sample = scripted_ds[0]
print(sample)
```

## License
The original dataset is released under the Creative Commons Attribution Non Commercial 4.0, a summary of the license can be found [here](https://creativecommons.org/licenses/by-nc/4.0/), and the full license can be found [here](https://creativecommons.org/licenses/by-nc/4.0/legalcode). 
This processed dataset follows the same license. For any usage that is not covered by this license, please contact [the dataset authors](https://psi.engr.tamu.edu/l2-arctic-corpus/).
Please also cite their paper if you use L2-ARCTIC for any publications,

```bibtex
@inproceedings{zhao2018l2arctic,
    author={Guanlong {Zhao} and Sinem {Sonsaat} and Alif {Silpachai} and Ivana {Lucic} and Evgeny {Chukharev-Hudilainen} and John {Levis} and Ricardo {Gutierrez-Osuna}},
    title={L2-ARCTIC: A Non-native English Speech Corpus},
    year=2018,
    booktitle={Proc. Interspeech},
    pages={2783–2787},
    doi={10.21437/Interspeech.2018-1110},
    url={http://dx.doi.org/10.21437/Interspeech.2018-1110}
}
```