Infant cry classification using an efficient graph structure and attention-based model

doi:10.1016/j.kjs.2024.100221

	Infant cry classification using an efficient graph structure and attention-based model
	Qiao, Xuesong 1; Jiao, Siwen 2; Li, Han 1; Liu, Gengyuan 1; Gao, Xuan 1; Li, Zhanshan 1
	2024-07-01
发表期刊	KUWAIT JOURNAL OF SCIENCE
ISSN	2307-4108
卷号	51 期号:3 页码:9
摘要	Crying serves as the primary means through which infants communicate, presenting a significant challenge for new parents in understanding its underlying causes. This study aims to classify infant cries to ascertain the reasons behind their distress. In this paper, an efficient graph structure based on multi -dimensional hybrid features is proposed. Firstly, infant cries are processed to extract various speech features, such as spectrogram, mel-scaled spectrogram, MFCC, and others. These speech features are then combined across multiple dimensions to better utilize the information in the cries. Additionally, in order to better classify the efficient graph structure, a local -to -global convolutional neural network (AlgNet) based on convolutional neural networks and attention mechanisms is proposed. The experimental results demonstrate that the use of the efficient graph structure improved the accuracy by an average of 8.01% compared to using standalone speech features, and the AlgNet model achieved an average accuracy improvement of 5.62% compared to traditional deep learning models. Experiments were conducted using the Dunstan baby language, Donate a cry, and baby cry datasets with accuracy rates of 87.78%, 93.83%, and 93.14% respectively.
关键词	Neural network Multi-head attention Infant cry Audio classification
DOI	10.1016/j.kjs.2024.100221
收录类别	SCI
语种	英语
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:001218519000001
出版者	ELSEVIER
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/38989
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Li, Zhanshan
作者单位	1.Jilin Univ, Coll Comp Sci & Technol, Changchun, Peoples R China 2.Inst Comp Technol, Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Qiao, Xuesong,Jiao, Siwen,Li, Han,et al. Infant cry classification using an efficient graph structure and attention-based model[J]. KUWAIT JOURNAL OF SCIENCE,2024,51(3):9.
APA	Qiao, Xuesong,Jiao, Siwen,Li, Han,Liu, Gengyuan,Gao, Xuan,&Li, Zhanshan.(2024).Infant cry classification using an efficient graph structure and attention-based model.KUWAIT JOURNAL OF SCIENCE,51(3),9.
MLA	Qiao, Xuesong,et al."Infant cry classification using an efficient graph structure and attention-based model".KUWAIT JOURNAL OF SCIENCE 51.3(2024):9.