--- 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: - 1K The initial release consist of test split with 1900 recordings and original transcriptions extracted from 10 publicly available datasets. ### Supported Tasks and Leaderboards The leaderboard with benchmark of publicly available ASR systems supporting Polish is [under construction](https://huggingface.co./spaces/michaljunczyk/pl-asr-bigos-benchmark/).
Evaluation results of 3 commercial and 5 freely available can be found in the [paper](https://annals-csis.org/proceedings/2023/drp/1609.html). ### Languages Polish ## Dataset Structure Dataset consists audio recordings in WAV format and corresponding metadata.
Audio and metadata can be used in raw format (TSV) or via hugging face datasets library. ### Data Instances 1900 audio files with original transcriptions are available in "test" split.
This consitutes 1.6% of the total available transcribed speech in 10 source datasets considered in the initial release. ### Data Fields Available fields: * file_id - file identifier * dataset_id - source dataset identifier * audio - binary representation of audio file * ref_original - original transcription of audio file * hyp_whisper_cloud - ASR hypothesis (output) from Whisper Cloud system * hyp_google_default - ASR hypothesis (output) from Google ASR system, default model * hyp_azure_default - ASR hypothesis (output) from Azure ASR system, default model * hyp_whisper_tiny - ASR hypothesis (output) from Whisper tiny model * hyp_whisper_base - ASR hypothesis (output) from Whisper base model * hyp_whisper_small - ASR hypothesis (output) from Whisper small model * hyp_whisper_medium - ASR hypothesis (output) from Whisper medium model * hyp_whisper_large - ASR hypothesis (output) from Whisper large (V2) model

Fields to be added in the next release: * ref_spoken - manual transcription in a spoken format (without normalization) * ref_written - manual transcription in a written format (with normalization) ### Data Splits Initial release contains only "test" split.
"Dev" and "train" splits will be added in the next release. ## 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. ### Source Data 10 datasets that meet the criteria were chosen as sources for the BIGOS dataset. * The Common Voice dataset (mozilla-common-voice-19) * The Multilingual LibriSpeech (MLS) dataset (fair-mls-20) * The Clarin Studio Corpus (clarin-pjatk-studio-15) * The Clarin Mobile Corpus (clarin-pjatk-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-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) #### 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.
To strike a balance in the evaluation dataset and to facilitate the comparison of Word Error Rate (WER) scores across multiple datasets, 200 samples are randomly selected from each corpus.
The only exception is ’pwr-azon-spont-20’, which contains significantly longer recordings and utterances, therefore only 100 samples are selected.
#### 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 Please refer to the [paper](https://www.researchgate.net/publication/374713542_BIGOS_-_Benchmark_Intended_Grouping_of_Open_Speech_Corpora_for_Polish_Automatic_Speech_Recognition) for more details. ### Annotations #### Annotation process Current release contains original transcriptions. Manual transcriptions 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 [BIGOS V1 paper](https://annals-csis.org/proceedings/2023/drp/1609.html). ### Contributions Thanks to [@goodmike31](https://github.com/goodmike31) for adding this dataset.