metadata

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 (Language DOcumentation REference COrpus) contains 100 hours of speech across 53 languages. It contains phonemic annotations using the sounds supported by X-SAMPA. You can read more about the Southern England portion here. 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 using this data processing script. This maps the phoneme annotations to IPA as supported by libraries like ipapy and panphon. 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

Request access to this dataset on the Hugging Face website. You will be automatically approved upon accepting the terms.
pip install datasets
Login to Hugging Face using huggingface-cli login with a token that has gated read access.
Use the dataset in your scripts:

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, and the full license can be found here. This processed dataset follows the same license.