DocumentCode
242924
Title
Application of neuro-fuzzy approaches to recognition and classification of infant cry
Author
Srijiranon, Krittakom ; Eiamkanitchat, Narissara
Author_Institution
Dept. of Comput. Eng., Chiang Mai Univ., Chiang Mai, Thailand
fYear
2014
fDate
22-25 Oct. 2014
Firstpage
1
Lastpage
6
Abstract
Languages are used as a tool for human to communicate their needs to one another. To be able to use any language human beings need time to learn to achieve understanding. The newborn babies use their cries by their instinct to communicate their needs. The difference cries of the infant can indicate different requirements. This work proposes a method to determine the meanings of infant cries according to the baby expert. It applies the novel Neuro-fuzzy techniques for the classification and Perceptual Linear Prediction for recognition the infant cries. The results showed that the classification performance obtained by using the Neuro-fuzzy yielded the most desirable accuracy than others popular methods. In addition, The Neuro-fuzzy structure designed in this paper can be applied to speech recognition of other further research.
Keywords
fuzzy neural nets; signal classification; speech recognition; classification performance; infant cry classification; infant cry recognition; neuro-fuzzy approach; perceptual linear prediction; speech recognition; Accuracy; Classification algorithms; Feature extraction; Mel frequency cepstral coefficient; Neural networks; Speech recognition; Support vector machine classification; Infant cry classification; Neuro-Fuzzy; Perceptual Linear Prediction (PLP);
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON 2014 - 2014 IEEE Region 10 Conference
Conference_Location
Bangkok
ISSN
2159-3442
Print_ISBN
978-1-4799-4076-9
Type
conf
DOI
10.1109/TENCON.2014.7022296
Filename
7022296
Link To Document