Hugging Face's logo

Datasets:
amu-cai
/
pl-asr-bigos-v2

Tasks:
Automatic Speech Recognition
Modalities:
Audio
Languages:
Polish
Size:
10K<n<100K
ArXiv:
Tags:
benchmark
polish
asr
speech
dataset
audio
DOI:
License:
Dataset card Files Community
3
pl-asr-bigos-v2 / README.md
mj-new
Updated README
37cc976
preview code
|
raw
history blame
12.9 kB
metadata
annotations_creators:
  - crowdsourced
  - expert-generated
  - other
  - machine-generated
language:
  - pl
language_creators:
  - crowdsourced
  - expert-generated
  - other
license:
  - cc-by-sa-4.0
multilinguality:
  - monolingual
pretty_name: pl-asr-bigos
size_categories:
  - 10K<n<100K
source_datasets:
  - original
  - extended|multilingual_librispeech
  - extended|common_voice
  - extended|minds14
  - extended|fleurs
tags:
  - benchmark
  - polish
  - asr
  - speech
  - dataset
  - audio
task_categories:
  - automatic-speech-recognition
task_ids: []
extra_gated_prompt: >-
  Original datasets used for curation of BIGOS have specific terms of usage that
  must be understood and agreed to before use. Below are the links to the
  license terms and datasets the specific license type applies to:

  * [Creative Commons
  0](https://creativecommons.org/share-your-work/public-domain/cc0) which
  applies to [Common
  Voice](https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0)

  * [Creative Commons By Attribution Share Alike
  4.0](https://creativecommons.org/licenses/by-sa/4.0/), which applies to
  [Clarin Cyfry](https://clarin-pl.eu/dspace/handle/11321/317), [Azon acoustic
  speech resources
  corpus](https://zasobynauki.pl/zasoby/korpus-nagran-probek-mowy-do-celow-budowy-modeli-akustycznych-dla-automatycznego-rozpoznawania-mowy,53293/).

  * [Creative Commons By Attribution
  3.0](https://creativecommons.org/licenses/by/3.0/), which applies to [CLARIN
  Mobile database](https://clarin-pl.eu/dspace/handle/11321/237), [CLARIN Studio
  database](https://clarin-pl.eu/dspace/handle/11321/236), [PELCRA Spelling and
  Numbers Voice Database](http://pelcra.pl/new/snuv) and [FLEURS
  dataset](https://huggingface.co/datasets/google/fleurs)

  * [Creative Commons By Attribution
  4.0](https://creativecommons.org/licenses/by/4.0/), which applies to
  [Multilingual
  Librispeech](https://huggingface.co/datasets/facebook/multilingual_librispeech)
  and [Poly AI Minds 14](https://huggingface.co/datasets/PolyAI/minds14)

  * [Proprietiary License of Munich AI Labs
  dataset](https://www.caito.de/2019/01/03/the-m-ailabs-speech-dataset)

  * Public domain mark, which applies to [PWR
  datasets](https://www.ii.pwr.edu.pl/~sas/ASR/)

  To use selected dataset, you also need to fill in the access forms on the
  specific datasets pages:

  * Common Voice:
  https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0
extra_gated_fields:
  I hereby confirm that I have read and accepted the license terms of datasets comprising BIGOS corpora: checkbox
  I hereby confirm that I have registered on the original Common Voice page and agree to not attempt to determine the identity of speakers in the Common Voice dataset: checkbox

Dataset Card for Polish ASR BIGOS corpora

Table of Contents

Dataset Description

Dataset Summary

The BIGOS (Benchmark Intended Grouping of Open Speech) corpora aims at simplifying the access and use of publicly available ASR speech datasets for Polish.

Supported Tasks and Leaderboards

Continous benchmark and leaderboard of PL ASR systems using BIGOS corpora is planned for 2024.

Languages

Polish

Dataset Structure

The datasets consist of audio recordings in the WAV format with corresponding metadata.
The audio and metadata can be used in a raw format (TSV) or via the Hugging Face datasets library.
References for the test split will only become available after the completion of the 2024 PolEval challenge.

Data Instances

The train set consists of 82 025 samples. The dev set consists of 14 254 samples The test set consists of 14 993 samples.

Data Fields

Available fields:

  • audioname - file identifier
  • split - test, validation or train split
  • dataset - source dataset identifier
  • ref_orig - original transcription of audio file
  • audio - HF dataset object with binary representation of audio file
  • samplingrate_orig - sampling rate of the original recording
  • sampling_rate - sampling rate of recording in the release
  • audio_duration_samples - duration of recordings in samples
  • audio_duration_seconds - duration of recordings in seconds
  • audiopath_bigos - relative filepath to audio file extracted from tar.gz archive
  • audiopath_local - absolute filepath to audio file extracted with the build script
  • speaker_gender - gender (sex) of the speaker extracted from the source meta-data (N/A if not available)
  • speaker_age - age group of the speaker (in CommonVoice format) extracted from the source (N/A if not available)
  • utt_length_words - length of the utterance in words
  • utt_length_chars - length of the utterance in characters
  • speech_rate_words - ratio of words to recording duration.
  • speech_rate_chars - ratio of characters to recording duration.



Data Splits

Train split contains recordings intendend for training. Validation split contains recordings for validation during training procedure. Test split contains recordings intended for evaluation only. References for test split are not available until the completion of 2024 PolEval challenge.

Subset train validation test
fair-mls-20 25 042 511 519
google-fleurs-22 2 841 338 758
mailabs-corpus_librivox-19 11 834 1 527 1 501
mozilla-common_voice_15-23 19 119 8 895 8 896
pjatk-clarin_studio-15 10 999 1 407 1 404
pjatk-clarin_mobile-15 2 861 242 392
polyai-minds14-21 462 47 53
pwr-maleset-unk 3 783 478 477
pwr-shortwords-unk 761 86 92
pwr-viu-unk 2 146 290 267
pwr-azon_read-20 1 820 382 586
pwr-azon_spont-20 357 51 48

Dataset Creation

Curation Rationale

Polish ASR Speech Data Catalog was used to identify suitable datasets which can be repurposed and included in the BIGOS corpora.
The following mandatory criteria were considered:

  • Dataset must be downloadable.
  • The license must allow for free, noncommercial use.
  • Transcriptions must be available and align with the recordings.
  • The sampling rate of audio recordings must be at least 8 kHz.
  • Audio encoding using a minimum of 16 bits per sample.

Recordings which either lacked transcriptions or were too short to be useful for training or evaluation were removed during curation.

Source Data

12 datasets that meet the criteria were chosen as sources for the BIGOS dataset.

  • The Common Voice dataset version 15 (mozilla-common_voice_15-23)
  • The Multilingual LibriSpeech (MLS) dataset (fair-mls-20)
  • The Clarin Studio Corpus (pjatk-clarin_studio-15)
  • The Clarin Mobile Corpus (pjatk-clarin_mobile-15)
  • The Jerzy Sas PWR datasets from Politechnika Wrocławska (pwr-viu-unk, pwr-shortwords-unk, pwr-maleset-unk). More info here
  • The Munich-AI Labs Speech corpus (mailabs-corpus-librivox-19)
  • The AZON Read and Spontaneous Speech Corpora (pwr-azon_spont-20, pwr-azon_read-20) More info here
  • The Google FLEURS dataset (google-fleurs-22)
  • The PolyAI minds14 dataset (polyai-minds14-21)

Initial Data Collection and Normalization

Source text and audio files were extracted and encoded in a unified format.
Dataset-specific transcription norms are preserved, including punctuation and casing.
In case of original dataset does not have test, dev, train splits provided, the splits were generated pseudorandomly during curation.

Who are the source language producers?

  1. Clarin corpora - Polish Japanese Academy of Technology
  2. Common Voice - Mozilla foundation
  3. Multlingual librispeech - Facebook AI research lab
  4. Jerzy Sas and AZON datasets - Politechnika Wrocławska
  5. Google - FLEURS
  6. PolyAI London - Minds14

Please refer to the BIGOS V1 paper for more details.

Annotations

Annotation process

Current release contains original transcriptions. Manual transcriptions of subsets and release of diagnostic dataset are planned for subsequent releases.

Who are the annotators?

Depends on the source dataset.

Personal and Sensitive Information

This corpus does not contain PII or Sensitive Information. All IDs pf speakers are anonymized.

Considerations for Using the Data

Social Impact of Dataset

To be updated.

Discussion of Biases

To be updated.

Other Known Limitations

The dataset in the initial release contains only a subset of recordings from original datasets.

Additional Information

Dataset Curators

Original authors of the source datasets - please refer to source-data for details.

Michał Junczyk ([email protected]) - curator of BIGOS corpora.

Licensing Information

The BIGOS corpora is available under Creative Commons By Attribution Share Alike 4.0 license.

Original datasets used for curation of BIGOS have specific terms of usage that must be understood and agreed to before use. Below are the links to the license terms and datasets the specific license type applies to:

Citation Information

Please cite using Bibtex

Contributions

Thanks to @goodmike31 for adding this dataset.