metadata
dataset_info:
features:
- name: speaker_id
dtype: string
- name: gender
dtype: string
- name: utterance_id
dtype: string
- name: language
dtype: string
- name: raw_text
dtype: string
- name: full_audio_file
dtype: string
- name: original_data_split
dtype: string
- name: region
dtype: string
- name: duration
dtype: float64
- name: start
dtype: int64
- name: end
dtype: float64
- name: utterance_audio_file
dtype: audio
- name: standardized_text
dtype: string
splits:
- name: test
num_bytes: 3046340447
num_examples: 15756
download_size: 2790946881
dataset_size: 3046340447
Dataset Card for NST Bokmål test (< 15 sec. segments)
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage:
- Repository: https://github.com/scribe-project/nodalida_2023_combined_training
- Paper:
@inproceedings{
solberg2023improving,
title={Improving Generalization of Norwegian {ASR} with Limited Linguistic Resources},
author={Per Erik Solberg and Pablo Ortiz and Phoebe Parsons and Torbj{\o}rn Svendsen and Giampiero Salvi},
booktitle={The 24rd Nordic Conference on Computational Linguistics},
year={2023}
}
- Point of Contact: Per Erik Solberg
Dataset Summary
This is the version of the Bokmål part of the Norwegian NST dataset used for testing the models in the paper Improving Generalization of Norwegian ASR with Limited Linguistic Resources presented at NoDaLiDa 2023. It only contains segments of a length < 15 sec and only the test set. For a full version of the NST, see this repository.
Languages
Norwegian Bokmål
Dataset Creation
Source Data
The full version of this dataset is found in the repository of the Norwegian Language Bank
Initial Data Collection and Normalization
The data was retrieved using the Spraakbanken downloader and standardized using the combined dataset standardization scripts. Bokmål segments with a duration < 15 seconds were extracted using this code.
Licensing Information
Citation Information
@inproceedings{
solberg2023improving,
title={Improving Generalization of Norwegian {ASR} with Limited Linguistic Resources},
author={Per Erik Solberg and Pablo Ortiz and Phoebe Parsons and Torbj{\o}rn Svendsen and Giampiero Salvi},
booktitle={The 24rd Nordic Conference on Computational Linguistics},
year={2023}
}