A Novel Method for Broiler Abnormal Sound Detection Using WMFCC and HMM
Joint Authors
Shen, Mingxia
Liu, Longshen
Li, Bo
Zhao, Ruqian
Yao, Wen
Yang, Ji
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-13
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Broilers produce abnormal sounds such as cough and snore when they suffer from respiratory diseases.
The aim of this research work was to develop a method for broiler abnormal sound detection.
The sounds were recorded in a broiler house for one week (24/7).
There were 20 thousand white feather broilers reared on the floor in a building.
Results showed that the developed recognition algorithm, using wavelet transform Mel frequency cepstrum coefficients (WMFCCs), correlation distance Fisher criterion (CDF), and hidden Markov model (HMM), provided an average accuracy, precision, recall, and F1 of 93.8%, 94.4%, 94.1%, and 94.2%, respectively, for broiler sound samples.
The results indicate that sound analysis can be used in broiler respiratory assessment in a commercial broiler farm.
American Psychological Association (APA)
Liu, Longshen& Li, Bo& Zhao, Ruqian& Yao, Wen& Shen, Mingxia& Yang, Ji. 2020. A Novel Method for Broiler Abnormal Sound Detection Using WMFCC and HMM. Journal of Sensors،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1190387
Modern Language Association (MLA)
Liu, Longshen…[et al.]. A Novel Method for Broiler Abnormal Sound Detection Using WMFCC and HMM. Journal of Sensors No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1190387
American Medical Association (AMA)
Liu, Longshen& Li, Bo& Zhao, Ruqian& Yao, Wen& Shen, Mingxia& Yang, Ji. A Novel Method for Broiler Abnormal Sound Detection Using WMFCC and HMM. Journal of Sensors. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1190387
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190387
