Infant cry classification using an efficient graph structure and attention-based model
文献类型：期刊论文
| 作者 | Qiao, Xuesong1; Jiao, Siwen2; Li, Han1; Liu, Gengyuan1; Gao, Xuan1; Li, Zhanshan1 |
| 刊名 | KUWAIT JOURNAL OF SCIENCE
 |
| 出版日期 | 2024-07-01 |
| 卷号 | 51期号:3页码:9 |
| 关键词 | Neural network Multi-head attention Infant cry Audio classification |
| ISSN号 | 2307-4108 |
| DOI | 10.1016/j.kjs.2024.100221 |
| 英文摘要 | 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. |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001218519000001 |
| 出版者 | ELSEVIER |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/38988]  |
| 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. |
入库方式： OAI收割
来源：计算技术研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。