README.md

metadata

license: mit
language:
  - es
  - eu
pretty_name: Albayzin 2024 Bilingual Basque-Spanish Speech to Text (BBS-S2T) Challenge

The Albayzin 2024 Bilingual Basque-Spanish Speech to Text (BBS-S2T) Challenge is based on the gttsehu/basque_parliament_1 dataset from Hugging Face. The database consists of four splits:

1. train : 749945 audio segments (automatically extracted)
2. train_clean : 661871 audio segments (automatically extracted)
3. validation : 4095 audio segments (manually validated)
4. test : 5152 audio segments (manually validated)

How to download the basque_parliament_1 database

1 - If you can handle yourself comfortably with Huggingface Datasets:

from datasets import load_dataset
ds = load_dataset("gttsehu/basque_parliament_1")

The Dataset contains four splits:

DatasetDict({
    train: Dataset({
        features: ['path', 'audio', 'sentence', 'speaker_id', 'language', 'PRR', 'length'],
        num_rows: 749945
    })
    train_clean: Dataset({
        features: ['path', 'audio', 'sentence', 'speaker_id', 'language', 'PRR', 'length'],
        num_rows: 661871
    })
    validation: Dataset({
        features: ['path', 'audio', 'sentence', 'speaker_id', 'language', 'PRR', 'length'],
        num_rows: 4095
    })
    test: Dataset({
        features: ['path', 'audio', 'sentence', 'speaker_id', 'language', 'PRR', 'length'],
        num_rows: 5152
    })
})

2 - Manual download:

git clone https://huggingface.co./datasets/gttsehu/basque_parliament_1

NOTE: git-lfs must be installed to be able to handle the download of the large tar files (which include the audio files).

Downloaded database structure:

basque_parliament_1/
├── audio
│   ├── dev_0.tar
│   ├── test_0.tar
│   ├── train_0.tar
│   ├── train_10.tar
│   ├── train_1.tar
│   ├── train_2.tar
│   ├── train_3.tar
│   ├── train_4.tar
│   ├── train_5.tar
│   ├── train_6.tar
│   ├── train_7.tar
│   ├── train_8.tar
│   └── train_9.tar
├── basque_parliament_1.py
├── languages.py
├── metadata
│   ├── dev.tsv
│   ├── test.tsv
│   ├── train_clean.tsv
│   └── train.tsv
├── README.md
└── release_stats.py

Untar all audio files:

ls basque_parliament_1/audio/*.tar | xargs -i tar -xC basque_parliament_1/audio -f {}