DocumentCode :
134293
Title :
GSOM-based modeling study on phoneme acquisition
Author :
Mengxue Cao ; Aijun Li ; Qiang Fang
Author_Institution :
Dept. of Linguistics, Grad. Sch. of Chinese Acad. of Social Sci., Beijing, China
fYear :
2014
fDate :
12-14 Sept. 2014
Firstpage :
432
Lastpage :
432
Abstract :
Summary form only given. Based on the Growing Self-Organizing Map (GSOM) modeling algorithm, by integrating optimized growing strategy and involving “cyclical reinforcing and reviewing training” procedure, we simulated phoneme acquisition of Standard German. The simulating result shows that the “cyclical reinforcing and reviewing training” procedure can improve learning quality of the network significantly; the modeling algorithm can acquire the vowel and manner of articulation categories and build the corresponding knowledge network in a proper way. The modeling result reveals that during language acquisition, children have the ability to utilize acoustic (spectrogram) features to acquire vowel categories and categories of different manners of articulation, and build acoustic space relations among different vowels.
Keywords :
acoustic signal processing; natural languages; self-organising feature maps; speech processing; GSOM modeling algorithm; Standard German; acoustic space relations; articulation category manner acquisition; cyclical reinforcing procedure; growing self-organizing map; knowledge network; language acquisition; network learning quality improvement; optimized growing strategy; phoneme acquisition; reviewing training procedure; vowel acquisition; growing self-organizing map; neurocomputational model; phoneme acquisition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Chinese Spoken Language Processing (ISCSLP), 2014 9th International Symposium on
Conference_Location :
Singapore
Type :
conf
DOI :
10.1109/ISCSLP.2014.6936686
Filename :
6936686
Link To Document :
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