README.md

---
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: ipa
    dtype: string
  - name: text
    dtype: string
  - name: id
    dtype: string
  - name: speaker_code
    dtype: string
  - name: speaker_age
    dtype: int64
  - name: speaker_gender
    dtype: string
  - name: recording_year
    dtype: int64
  - name: recoding_topic
    dtype: string
  - name: sound_quality
    dtype: string
  - name: background_noise
    dtype: string
  splits:
  - name: train
    num_bytes: 90872785
    num_examples: 577
  download_size: 90824053
  dataset_size: 90872785
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
language:
- en
tags:
- Speech
- IPA
- Southern British
pretty_name: DoReCo Southern British
size_categories:
- 1K<n<10K
---

# DoReCo Southern England
[DoReCo](https://doreco.huma-num.fr/) (Language DOcumentation REference COrpus) contains 100 hours of speech across 53 languages.
It contains phonemic annotations using the sounds supported by [X-SAMPA](https://en.wikipedia.org/wiki/X-SAMPA).
You can read more about the Southern England portion [here](https://doreco.huma-num.fr/languages/sout3282). 
It was compiled by Nils Norman Schiborr and further processed by Ludger Paschen and Matthew Stave.

## 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/DoReCo.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 split up the longer narrative recordings into shorter self-contained clips based on semantic content and remove unintelligible utterances with less than 11 phonemes.

- The dataset has 577 samples (around 47 minutes of 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/DoReCo) 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_ds = load_dataset("KoelLabs/DoReCo")['train']

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

## License
The original dataset is released under the Creative Commons Attribution 4.0, a summary of the license can be found [here](https://creativecommons.org/licenses/by/4.0/), and the full license can be found [here](https://creativecommons.org/licenses/by/4.0/legalcode.en). 
This processed dataset follows the same license.