Datasets:
Tasks:
Automatic Speech Recognition
Formats:
parquet
Languages:
Danish
Size:
1M - 10M
ArXiv:
License:
File size: 4,246 Bytes
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---
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<n<1M
license: other
---
# Dataset Card for FT Speech
## Dataset Description
- **Repository:** <https://ftspeech.github.io/>
- **Point of Contact:** [Dan Saattrup Nielsen](mailto:[email protected])
- **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
#### Transcription Length Distribution
## 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}
}
``` |