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 :
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