The dataset viewer is not available because its heuristics could not detect any supported data files. You can try uploading some data files, or configuring the data files location manually.

Albayzin 2024 Bilingual Basque-Spanish Speech to Text (BBS-S2T) Challenge

see Albayzin_2024_BBS-S2T_EvalPlan for a description of the challenge.

NOTE: Test data will be released on September 2nd, 2024.

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

  1. train : 749945 audio segments (automatically extracted)
  2. train_clean : 661871 audio segments (automatically extracted, highly reliable transcriptions)
  3. dev : 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
    })
})

NOTE: The validation split corresponds with the dev split of this challenge.

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

Untar all audio files:

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

The metadata directory contains the index files for the 4 splits. Each index file contains five tab separated fields:

  1. The audio file path
  2. The language of the segment (es: spanish, eu: basque and bi: bilingual)
  3. The speaker id
  4. The PhoneRecognitionRate indicating the quality of the transcription
  5. The length of the segment (in seconds)
  6. The transcription
path    language        speaker_id      PRR     length  sentence
10-007_20130124_01/10-007_20130124_01_83.92_93.84.mp3   eu      0       100.00  9.92    egun on guztioi bilkurari hasiera emango diogu gai zerrendako lehenengo puntua bateraezintasunen
10-007_20130124_01/10-007_20130124_01_95.49_105.34.mp3  eu      416     100.00  9.85    euskadiren izeneko senatari izendatzeko hautagaien bateragarritasun egoerari buruz eztabaida eta behin betiko ebazpena eta hala badagokio senatariak
10-007_20130124_01/10-007_20130124_01_105.35_112.10.mp3 eu      416     98.46   6.75    hautatzeko botazioa batzordeko kidearen batek irizpidearen alde hitz egin nahi du
10-007_20130124_01/10-007_20130124_01_117.61_127.29.mp3 eu      416     100.00  9.68    aurka hitz egin nahi du bost minutuko txanda daukazue eta mistoa upyd hasiko da maneiro
10-007_20130124_01/10-007_20130124_01_149.82_160.12.mp3 es      290     100.00  10.30   buenos dΓ­as a todas y a todos utilizo este turno para alzar la voz ante la pretensiΓ³n de eh bildu de que
...
Downloads last month
51