Genetic Programming for Automatic Stress Detection in Spoken English

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{xie:evows06,

• author = "Huayang Xie and Mengjie Zhang and Peter Andreae",
• title = "Genetic Programming for Automatic Stress Detection in Spoken English",
• booktitle = "Applications of Evolutionary Computing, EvoWorkshops2006: {EvoBIO}, {EvoCOMNET}, {EvoHOT}, {EvoIASP}, {EvoInteraction}, {EvoMUSART}, {EvoSTOC}",
• year = "2006",
• month = "10-12 " # apr,
• editor = "Franz Rothlauf and Jurgen Branke and Stefano Cagnoni and Ernesto Costa and Carlos Cotta and Rolf Drechsler and Evelyne Lutton and Penousal Machado and Jason H. Moore and Juan Romero and George D. Smith and Giovanni Squillero and Hideyuki Takagi",
• series = "LNCS",
• volume = "3907",
• publisher = "Springer Verlag",
• address = "Budapest",
• publisher_address = "Berlin",
• ISBN = "3-540-33237-5",
• keywords = "genetic algorithms, genetic programming",
• pages = "460--471",
• DOI = "doi:10.1007/11732242_41",
• abstract = "an approach to the use of genetic programming (GP) for the automatic detection of rhythmic stress in spoken New Zealand English. A linear-structured GP system uses speaker independent prosodic features and vowel quality features as terminals to classify each vowel segment as stressed or unstressed. Error rate is used as the fitness function. In addition to the standard four arithmetic operators, this approach also uses several other arithmetic, trigonometric, and conditional functions in the function set. The approach is evaluated on 60 female adult utterances with 703 vowels and a maximum accuracy of 92.61% is achieved. The approach is compared with decision trees (DT) and support vector machines (SVM). The results suggest that, on our data set, GP outperforms DT and SVM for stress detection, and GP has stronger automatic feature selection capability than DT and SVM.",
• notes = "part of \cite{evows06} also known as \cite{conf/evoW/XieZA06} See also \cite{Andreae:2008:IJKBIES}",

}

Genetic Programming entries for Huayang Jason Xie Mengjie Zhang Peter Andreae

Citations