Dataset Card for Voxpopuli

Dataset Summary

VoxPopuli is a large-scale multilingual speech corpus for representation learning, semi-supervised learning and interpretation. The raw data is collected from 2009-2020 European Parliament event recordings. We acknowledge the European Parliament for creating and sharing these materials. This implementation contains transcribed speech data for 18 languages. It also contains 29 hours of transcribed speech data of non-native English intended for research in ASR for accented speech (15 L2 accents)

Example usage

VoxPopuli contains labelled data for 18 languages. To load a specific language pass its name as a config name:

from datasets import load_dataset

voxpopuli_croatian = load_dataset("facebook/voxpopuli", "hr")

To load all the languages in a single dataset use "multilang" config name:

voxpopuli_all = load_dataset("facebook/voxpopuli", "multilang")

To load a specific set of languages, use "multilang" config name and pass a list of required languages to languages parameter:

voxpopuli_slavic = load_dataset("facebook/voxpopuli", "multilang", languages=["hr", "sk", "sl", "cs", "pl"])

To load accented English data, use "en_accented" config name:

voxpopuli_accented = load_dataset("facebook/voxpopuli", "en_accented")

Note that L2 English subset contains only test split.

Supported Tasks and Leaderboards

automatic-speech-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). The model is presented with an audio file and asked to transcribe the audio file to written text. The most common evaluation metric is the word error rate (WER).

Accented English subset can also be used for research in ASR for accented speech (15 L2 accents)

Languages

VoxPopuli contains labelled (transcribed) data for 18 languages:

Language	Code	Transcribed Hours	Transcribed Speakers	Transcribed Tokens
Italian	It	91	306	757K

Accented speech transcribed data has 15 various L2 accents:

Accent	Code	Transcribed Hours	Transcribed Speakers
Italian	en_it	1.11	15

Dataset Structure

Data Instances

{
  'audio_id': '20180206-0900-PLENARY-15-hr_20180206-16:10:06_5',
  'language': 11,  # "hr"
  'audio': {
    'path': '/home/polina/.cache/huggingface/datasets/downloads/extracted/44aedc80bb053f67f957a5f68e23509e9b181cc9e30c8030f110daaedf9c510e/train_part_0/20180206-0900-PLENARY-15-hr_20180206-16:10:06_5.wav',
    'array': array([-0.01434326, -0.01055908,  0.00106812, ...,  0.00646973], dtype=float32),
    'sampling_rate': 16000
  },
  'raw_text': '',
  'normalized_text': 'poast genitalnog sakaenja ena u europi tek je jedna od manifestacija takve tetne politike.',
  'gender': 'female',
  'speaker_id': '119431',
  'is_gold_transcript': True,
  'accent': 'None'
}

Data Fields

audio_id (string) - id of audio segment
language (datasets.ClassLabel) - numerical id of audio segment
audio (datasets.Audio) - a dictionary containing the path to the audio, the decoded audio array, and the sampling rate. In non-streaming mode (default), the path points to the locally extracted audio. In streaming mode, the path is the relative path of an audio inside its archive (as files are not downloaded and extracted locally).
raw_text (string) - original (orthographic) audio segment text
normalized_text (string) - normalized audio segment transcription
gender (string) - gender of speaker
speaker_id (string) - id of speaker
is_gold_transcript (bool) - ?
accent (string) - type of accent, for example "en_lt", if applicable, else "None".

Data Splits

All configs (languages) except for accented English contain data in three splits: train, validation and test. Accented English en_accented config contains only test split.

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

The raw data is collected from youtube

Who are the source language producers?

Speakers are participants of the European Parliament events, many of them are EU officials.