Birdsong recognition using prediction-based recurrent neural fuzzy networks

Neurocomputing

Volumn 71, Issue 1-3, 2007, Pages 121-130

  Juang, Chia Feng ^a   Chen, Tai Mou ^a  

^a NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

Author keywords

Bird species identification; LPC coefficients; Neural networks; Recurrent fuzzy systems; Temporal sequence prediction

Indexed keywords

BACKPROPAGATION; FEATURE EXTRACTION; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; PATTERN RECOGNITION;

BIRD SPECIES IDENTIFICATION; LINEAR PREDICTIVE CODING COEFFICIENTS; RECURRENT FUZZY SYSTEMS; TEMPORAL SEQUENCE PREDICTION;

RECURRENT NEURAL NETWORKS;

ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATIC SPEECH RECOGNITION; BIRD; CONTROLLED STUDY; ENVIRONMENTAL FACTOR; FUZZY SYSTEM; HUMAN; LEARNING; MATHEMATICAL COMPUTING; NONHUMAN; PREDICTION; PRIORITY JOURNAL; SIGNAL NOISE RATIO; SPEECH; TAIWAN; TASK PERFORMANCE; TRAINING; VOCAL CORD;

EID: 35649011886     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2007.08.011     Document Type: Article

References (19)

1. Anderson S.E., Dave A.S., and Margoliash D. Template-based automatic recognition of birdsong syllables from continuous recordings. J. Acoust. Soc. Am. 100 (1996) 1209-1219
2. Catchpole C.A., and Slater P.J.B. Bird Song: Biological Themes and Variations (1995), Cambridge University Press, Cambridge, UK
3. CD title: Internet of birds, CD number: TCD-5032, Wind Records Co., Ltd., Taiwan, 1999.
4. Date E.M., Lemon R.E., Weary D.M., and Richter A.K. Species identity by birdsong: discrete or additive information?. Anim. Behav. 41 (1991) 111-120
5. A. Härmä, Automatic identification of bird species based on sinusoidal modeling of syllables, in: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, 2003, pp. 545-548.
6. Juang C.F. A TSK-type recurrent fuzzy network for dynamic systems processing by neural network and genetic algorithm. IEEE Trans. Fuzzy Syst. 10 2 (2002) 155-170
7. Juang C.F., and Ku S.J. A recurrent fuzzy network for fuzzy temporal sequence processing and gesture recognition. IEEE Trans. Syst. Man Cybern. 35 3 (2005) 646-658
8. C. Kwan, et al., Bird song classification algorithms theory and experimental results, in: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, 2004, pp. 289-292.
9. Lee C.H., and Teng C.C. Identification and control of dynamic systems using recurrent fuzzy neural networks. IEEE Trans. Fuzzy Syst. 8 4 (2000) 349-366
10. Mastorocostas P.A., and Theocharis J.B. A recurrent fuzzy-neural model for dynamic system identification. IEEE Trans. Syst. Man Cybern. 32 2 (2002) 176-190
11. McIlraith A.L., and Card H.C. Birdsong recognition using backpropagation and multivariate statistics. IEEE Trans. Signal Process. 45 11 (1997) 2740-2748
12. Mouzouri G.C., and Mendel J.M. Dynamic nonsingleton fuzzy logic systems for nonlinear modeling. IEEE Trans. Fuzzy Syst. 5 2 (1997) 199-208
13. Rabiner L., and Juang B.H. Fundamentals of Speech Recognition (1993), Prentice-Hall, Englewood Cliffs, NJ
14. J. Tebelskis, A. Waibel, Large vocabulary recognition using linked predictive neural networks, in: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, 1990, pp. 437-440.
15. Theocharis J.B. A high-order recurrent neuro-fuzzy system with internal dynamics: application to the adaptive noise cancellation. Fuzzy Sets Syst. 157 4 (2006) 471-500
16. Thompson N.S., LeDoux K., and Moody K. A system for describing bird song units. Bioacoustics 5 (1994) 267-279
17. Wang Y.C., Chien C.J., and Teng C.C. Direct adaptive iterative learning control of nonlinear systems using an output-recurrent fuzzy neural network. IEEE Trans. Syst. Man Cybern. 34 3 (2004) 1348-1359
18. Williams R.J., and Zipser D. A learning algorithm for continually running recurrent network. Neural Comput. 1 2 (1989) 270-280
19. Zhang J., and Morris A.J. Recurrent neuro-fuzzy networks for nonlinear process modeling. IEEE Trans. Neural Networks 10 2 (1999) 313-326