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오류신고
- 데이터 정보
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오류신고를 진행 하실 데이터 정보를 담은 표입니다. 제목(Main) Coughs: ESC-50 and FSDKaggle2018 제목(Sub) 저자 Abdelkhalek, Mahmoud;Jinyi Qiu;Hernandez, Michelle;Bozkurt, Alper;Lobaton, Edgar; 제공처 OpenAIRE 리포지터리 OpenAIRE
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오류신고 접수 정보를 담은 표이며, 메일주소, 오류내용을 입력합니다. 아이디 오류신고 접수 정보를 담은 표이며, 메일주소, 오류내용을 입력합니다.오류 구분 - 개인정보 노출방지를 위해 개인정보 내용은 가급적 자제하여 주시기 바랍니다.
- 일방적인 욕설 및 부정적인 내용 작성시 원작자의 판단에 따라 신고자에게 피해가 발생할 수 있습니다. 깨끗하고 청렴한 서비스 문화를 위해 필요한 정보만 기재해주시면 감사하겠습니다.
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2021
해외
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CC-BY-4.0
English
Coughs: ESC-50 and FSDKaggle2018
Coughs: ESC-50 and FSDKaggle2018 Abdelkhalek, Mahmoud;Jinyi Qiu;Hernandez, Michelle;Bozkurt, Alper;Lobaton, Edgar;
This dataset consists of timestamps for coughs contained in files extracted from the ESC-50 and FSDKaggle2018 datasets. Citation This dataset was generated and used in our paper: Mahmoud Abdelkhalek, Jinyi Qiu, Michelle Hernandez, Alper Bozkurt, Edgar Lobaton, “Investigating the Relationship between Cough Detection and Sampling Frequency for Wearable Devices,” in the 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2021. Please cite this paper if you use the timestamps.csv file in your work. Generation The cough timestamps given in the timestamps.csv file were generated using the cough templates given in figures 3 and 4 in the paper: A. H. Morice, G. A. Fontana, M. G. Belvisi, S. S. Birring, K. F. Chung, P. V. Dicpinigaitis, J. A. Kastelik, L. P. McGarvey, J. A. Smith, M. Tatar, J. Widdicombe, ERS guidelines on the assessment of cough, European Respiratory Journal 2007 29: 1256-1276; DOI: 10.1183/09031936.00101006 More precisely, 40 files labelled as coughing in the ESC-50 dataset and 273 files labelled as Cough in the FSDKaggle2018 dataset were manually searched using Audacity for segments of audio that closely matched the aforementioned templates, both visually and auditorily. Some files did not contain any coughs at all, while other files contained several coughs. Therefore, only the files that contained at least one cough are included in the coughs directory. In total, the timestamps of 768 cough segments with lengths ranging from 0.2 seconds to 0.9 seconds were extracted. Description The audio files are presented in wav format in the coughs directory. Files named in the general format of *-*-*-24.wav were extracted from the ESC-50 dataset, while all other files were extracted from the FSDKaggle2018 dataset. The timestamps.csv file contains the timestamps for the coughs and it consists of four columns:
file_name,cough_number,start_time,end_time
Files in the file_name column can be found in the coughs directory. cough_number refers to the index of the cough in the corresponding file. For example, if the file X.wav contains 5 coughs, then X.wav will be repeated 5 times under the file_name column, and for each row, the cough_number will range from 1 to 5. start_time refers to the starting time of a cough segment measured in seconds, while end_time refers to the end time of a cough segment measured in seconds. Licensing The ESC-50 dataset as a whole is licensed under the Creative Commons Attribution-NonCommercial license. Individual files in the ESC-50 dataset are licensed under different Creative Commons licenses. For a list of these licenses, see LICENSE. The ESC-50 files in the cough directory are given for convenience only, and have not been modified from their original versions. To download the original files, see the ESC-50 dataset. The FSDKaggle2018 dataset as a whole is licensed under the Creative Commons Attribution 4.0 International license. Individual files in the FSDKaggle2018 dataset are licensed under different Creative Commons licenses. For a list of these licenses, see the License section in FSDKaggle2018. The FSDKaggle2018 files in the cough directory are given for convenience only, and have not been modified from their original versions. To download the original files, see the FSDKaggle2018 dataset. The timestamps.csv file is licensed under the Creative Commons Attribution-NonCommercial 4.0 International license.;This work was supported by the National Science Foundation under award IIS-1915599 and EEC-1160483 (ERC for ASSIST).
This work was supported by the National Science Foundation under award IIS-1915599 and EEC-1160483 (ERC for ASSIST).
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원문정보
- http://dx.doi.org/10.5281/zenodo.5136592 https://dx.doi.org/10.5281/zenodo.5136592 https://dx.doi.org/10.5281/zenodo.5136591
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