MFCC Feature Selection for Infant Cry Classification
Author:
Affiliation:
1. Thammasat University,Faculty of Science and Technology,Department of Computer Science,Pathumthani,Thailand
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10049307/10049308/10049328.pdf?arnumber=10049328
Reference10 articles.
1. A Comparative Study of MFCC and LPCC Features For Speech Activity Detection Using Deep Belief Network
2. LPC and LPCC method of feature extraction in Speech Recognition System
3. Decision Tree based Sleep Stage Estimation from Nocturnal Audio Signals;deng;International Conference on Digital Signal Processing (DSP),2022
4. Infant Cry Language Analysis and Recognition: An Experimental Approach;wu;IEEE/CAA Journal of Automatica Sinica,2019
5. Automatic methods for infant cry classification
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. From Cries to Answers: A Comprehensive CNN+DNN Hybrid Model for Infant Cry Classification with Enhanced Data Augmentation and Feature Extraction;2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS);2024-03-08
2. Analysis of Multiple Types of Baby Cries Based on LSTM;2023 8th International Conference on Intelligent Computing and Signal Processing (ICSP);2023-04-21
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