--- dataset_info: features: - name: utterance_id dtype: string - name: speaker_gender dtype: string - name: sentence dtype: string - name: speaker_id dtype: string - name: audio dtype: audio: sampling_rate: 16000 splits: - name: train num_bytes: 209434570129.268 num_examples: 995677 - name: dev_balanced num_bytes: 579692770.829 num_examples: 2601 - name: dev_other num_bytes: 1725502342.095 num_examples: 7595 - name: test_balanced num_bytes: 1158740779.222 num_examples: 5534 - name: test_other num_bytes: 1254987645.527 num_examples: 5837 download_size: 101776974871 dataset_size: 214153493666.941 task_categories: - automatic-speech-recognition language: - da pretty_name: FT Speech size_categories: - 100K - **Point of Contact:** [Dan Saattrup Nielsen](mailto:dan.nielsen@alexandra.dk) - **Size of downloaded dataset files:** 101.78 GB - **Size of the generated dataset:** 214.15 GB - **Total amount of disk used:** 315.93 GB ### Dataset Summary This dataset is an upload of the [FT Speech dataset](https://ftspeech.github.io/). The training, validation and test splits are the original ones. ### Supported Tasks and Leaderboards Training automatic speech recognition is the intended task for this dataset. No leaderboard is active at this point. ### Languages The dataset is available in Danish (`da`). ## Dataset Structure ### Data Instances - **Size of downloaded dataset files:** 101.78 GB - **Size of the generated dataset:** 214.15 GB - **Total amount of disk used:** 315.93 GB An example from the dataset looks as follows. ``` { 'utterance_id': 'S001_20151_M012_P00034-2', 'speaker_gender': 'F', 'sentence': 'alle de fem tekniske justeringer der er en del af lovforslaget', 'speaker_id': 'S001', 'audio': { 'path': 'S001_20151_M012_P00034-2.wav', 'array': array([-3.75366211e-03, -5.27954102e-03, -3.87573242e-03, ..., 9.15527344e-05, -1.52587891e-04, 5.79833984e-04]), 'sampling_rate': 16000 } } ``` ### Data Fields The data fields are the same among all splits. - `utterance_id`: a `string` feature. - `speaker_gender`: a `string` feature. - `sentence`: a `string` feature. - `speaker_id`: a `string` feature. - `audio`: an `Audio` feature. ### Dataset Statistics There are 995,677 samples in the training split, 2,601 in the dev_balanced split, 7,595 in the dev_other split, 5,534 in the test_balanced and 5,837 in the test_other split. #### Speakers There are 374 unique speakers in the training dataset, 20 unique speakers in the validation dataset and 40 unique speakers in the test dataset. None of the dataset splits share any speakers. #### Gender Distribution ![ftspeech-gender-distribution.png](https://cdn-uploads.huggingface.co/production/uploads/60d368a613f774189902f555/0h_L7-riNfQbKFdYWgy01.png) #### Transcription Length Distribution ![ftspeech-length-distribution.png](https://cdn-uploads.huggingface.co/production/uploads/60d368a613f774189902f555/z1MqsvACrY_8XNXAx0UcD.png) ## Dataset Creation ### Curation Rationale There are not many large-scale ASR datasets in Danish. ### Source Data The data constitutes public recordings of sessions from the Danish Parliament, along with manual transcriptions. ## Additional Information ### Dataset Curators Andreas Kirkedal, Marija Stepanović and Barbara Plank curated the dataset as part of their FT Speech paper (see citation below). [Dan Saattrup Nielsen](https://saattrupdan.github.io/) from the [The Alexandra Institute](https://alexandra.dk/) reorganised the dataset and uploaded it to the Hugging Face Hub. ### Licensing Information The dataset is licensed under [this custom license](https://www.ft.dk/da/aktuelt/tv-fra-folketinget/deling-og-rettigheder). ### Citation ``` @inproceedings{ftspeech, author = {Kirkedal, Andreas and Stepanović, Marija and Plank, Barbara}, title = {{FT Speech: Danish Parliament Speech Corpus}}, booktitle = {Proc. Interspeech 2020}, year = {2020}, url = {arxiv.org/abs/2005.12368} } ```