Abstract
Bengalese Finch (shape Lonchura striata var. domestica) sings more sophisticated songs than other birds and the grammar of their songs has been found to be described with probabilistic finite state automaton (PFA). In the present paper, we propose a multilayer neural network model that succeeds in reproducing the qualitatively similar symbol sequence by taking into account the memory process. The use of the present method is illustrated for the songs of Bengalese Finch with particular emphasis on issues of input delay that is necessary to obtain the correct grammar. It is found that the grammar obtained from the simulated symbol sequence using the PFA agrees well with the real one.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Okanoya, K.: The Bengalese Finch: A window on the behavioral neurobiology of birdsong syntax. Behavioral Neurobiology of Birdsong, 1016 (2004) 724–735.
Honda, E., Okanoya, K.: Acoustical and syntactical comparisons between songs of the White-backed Munia (Lonchura striata) and its domesticated strain, the Bengalese Finch (Lonchura striata var. domestica)(Biochemistry). Zoological Science, 16 (1999) 319–326.
Hoshino, T., Okanoya, K.: Lesion of a higher-order song nucleus disrupts phrase level complexity in Bengalese finches. Neuroreport, 11 (2000) 2091–2095.
Simon, H.: Neural Networks: A Comprehensive Foundation. Prentice hall (1999).
Dana, R., Yoram S., Naftali, T.: The power of amnesia: Learning probabilistic automata with variable memory length. Machine Learning, 25 (1996) 117–150.
Kita, K.: Computation and Language Volume 4: Probabilistic Language Model. University of Tokyo Press (in Japanese) (1999).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kotani, J., Mori, Y., Matsuba, I. (2008). Neural Network Model Generating Symbol Sequence for Songs of Bengalese Finch. In: Wang, R., Shen, E., Gu, F. (eds) Advances in Cognitive Neurodynamics ICCN 2007. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8387-7_25
Download citation
DOI: https://doi.org/10.1007/978-1-4020-8387-7_25
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-8386-0
Online ISBN: 978-1-4020-8387-7
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)