--- 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 ### Supported Tasks and Leaderboards * Open Polish ASR challenge [PolEval](http://poleval.pl/) using BIGOS V2 and [PELCRA for BIGOS](https://huggingface.co/datasets/pelcra/pl-asr-pelcra-for-bigos) datasets * Evaluation of 3 commercial and 5 freely available on [BIGOS V1](https://huggingface.co/datasets/michaljunczyk/pl-asr-bigos) [(paper)](https://annals-csis.org/proceedings/2023/drp/1609.html). 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 23/24 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 * `audio` - binary representation of audio file * `ref_orig` - original transcription of audio file * `samplingrate_orig` - sampling rate of the original recording * `sampling_rate` - sampling rate of recording in the release * `audiopath_bigos` - audio filepath after extraction of tar.gz archive

### 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 23/24 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](https://github.com/goodmike31/pl-asr-speech-data-survey) 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](https://www.ii.pwr.edu.pl/) * 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](https://zasobynauki.pl/zasoby/korpus-nagran-probek-mowy-do-celow-budowy-modeli-akustycznych-dla-automatycznego-rozpoznawania-mowy) * 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](https://annals-csis.org/proceedings/2023/drp/1609.html) 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](#source-data) for details. Michał Junczyk (michal.junczyk@amu.edu.pl) - curator of BIGOS corpora. ### Licensing Information The BIGOS corpora is available under [Creative Commons By Attribution Share Alike 4.0 license.](https://creativecommons.org/licenses/by-sa/4.0/) 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/) ### Citation Information Please cite using [Bibtex](https://dblp.org/rec/conf/fedcsis/Junczyk23.html?view=bibtex) ### Contributions Thanks to [@goodmike31](https://github.com/goodmike31) for adding this dataset.