NNARX Model of Speech Signal Generating System: Test Error Subject to Modeling Mode Selection

This paper presents comparative analysis of different processing errors when modeling speech signal generating system simulated by neural network auto regressive with extra input (NNARX). Feed forward NNs were used. Vowels were taken to train and test models. Gradient descent algorithm (GDA) is used...

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Bibliographic Details
Published in2006 25th International Conference on Microelectronics pp. 643 - 646
Main Authors Protic, D., Milosavljevic, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2006
Subjects
Analytical models
Biological neural networks
Brain modeling
Feeds
Signal analysis
Signal generators
Signal processing
Speech analysis
Speech processing
System testing
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ISBN9781424401178
1424401178
DOI10.1109/ICMEL.2006.1651050

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Summary:This paper presents comparative analysis of different processing errors when modeling speech signal generating system simulated by neural network auto regressive with extra input (NNARX). Feed forward NNs were used. Vowels were taken to train and test models. Gradient descent algorithm (GDA) is used for the training, back propagation algorithm (BPA) for the testing, and optimal brain surgeon (OBS) for the NN pruning. Results are given in Tables I-IV, and compared in conclusion
ISBN:9781424401178
1424401178
DOI:10.1109/ICMEL.2006.1651050