Method and apparatus for automatically identifying animal...

Data processing: speech signal processing – linguistics – language – Speech signal processing – Recognition

Reexamination Certificate

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C704S243000, C704S246000, C704S270000, C119S713000, C119S718000

Reexamination Certificate

active

07454334

ABSTRACT:
Relatively powerful hand-held computing devices, Digital Signal Processors, Audio signal processing technology, voice recognition technology, expert systems, Hidden Markov Models, and/or neural networks are employed in a device capable of real-time automated species identification by listening to bird vocalizations in the field, analyzing their waveforms, and comparing these waveforms against known reference samples. An apparatus for identifying animal species from their vocalizations, comprises a source of digital signal representative of at least one animal candidate vocalization; a feature extractor that receives the digital signal, recognizes notes therein and extracts phrases including plural notes and that produces a parametric representation of the extracted phrases; and a comparison engine that receives the parametric representation of at least one of the digital signal and the extracted phrases, and produces an output signal representing information about the animal candidate based on a likely match between the animal candidate vocalization and known animal vocalizations. A computer-implemented method of identifying animal species, comprises: obtaining a digital signal representing a vocalization by a candidate animal; transforming the digital signal into a parametric representation thereof; extracting from the parametric representation a sequence of notes defining a phrase; comparing the phrase to phrases known to be produced by a plurality of possible animal species; and identifying a most likely match for the vocalization by the candidate animal based upon the comparison. The comparison engine or comparison function may use Hidden Markov Models, expert systems and/or neural networks.

REFERENCES:
patent: 5452364 (1995-09-01), Bonham
patent: 5956463 (1999-09-01), Patrick et al.
patent: 6546368 (2003-04-01), Weninger et al.
patent: 7082394 (2006-07-01), Burges et al.
patent: 2001/0044719 (2001-11-01), Casey
patent: 2003/0125946 (2003-07-01), Hsu
patent: 2004/0107104 (2004-06-01), Schaphorst
patent: 2 089 597 (1994-08-01), None
patent: 0 629 996 (1994-12-01), None
Clemins, P. Johnson, M. “Application of speech recognition to african elephant vocalizations” Acoutics, Speech and Signal Processing vol. 1, Apr. 2003, pp. 484-487.
Franzen, A. Gu, I. “Classification of bird species by using key song searching: a comparative study” Systems, Man and Cybernetics, vol. 1, Oct. 2003, pp. 880-887.
Anderson, S. Dave, A. Margoliash, D. “Template-based automatic recognition of birdsong syllables from continuous recordings.” J. Acoust. Soc. Am. 100, pt. 1, Aug. 1996.
Kogan, J. Maroliash, D. “Automated recognition of bird song elements from continuous recordings using dynamic time warping and HHM: A comparative study” J. Acoustic Soc. Am. 103, Apr. 1998.
Harma, A. “Automatic identification of bird species based on sinusoidal modelling of syllables.” IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 5, pp. 545-548, Apr. 2003.
Anderson, S.E., et al., Department of Organismal Biology and Anatomy, University of Chicago, Speech Recognition Meets Bird Song: A Comparison of Statistics-Based and Template-Based Techniques, JASA, vol. 106, No. 4, Pt. 2, Oct. 1999.
Anonymous, The Basics of Microphones, Apr. 26, 2003, pp. 1-4, http://www.nrgresearch.com/microphonestutorial.htm.
Lleida, L. et al., Robust Continuous Speech Recognition System Based on a Microphone Array, IEEE International Conference on Seattle, WA, pp. 241-244, May 12, 1998.
Suksmono, A.B., et al., Adaptive Image Coding Based on Vector Quantization Using SOFM-NN Algorithm, IEEE APCCAS (Asia-Pacific Conference on Chiangmai, Thailand, pp. 443-446, Nov. 1998.
El Gayar, N. et al., Fuzzy Neural Network Models for High-Dimensional Data Clustering, ISFL '97, Second International ICSC Sumposium on Fuzzy Logical and Applications ICSC Academic Press, Zurich, Switzerland, pp. 203-209, Feb. 12, 1997.
Mcilraith, Alex L. and Card, Howard C., Birdsong Recognition Using Backpropagation and Multivariate Statistics, IEEE Transactions on Signal Processing, vol. 45, No. 11, Nov. 1997.
http://ourworld.compuserve.com/homepages/G—Kunkel/project/Project.htm Jun. 22, 2004.
Harma, Aki, “Automatic Identification of Bird Species Based pm Sinusoidal Modeling of Syllables”, IEEE Int. Conf. Acoustics, Speech, Signal Processing (ICASSP 2003), Hong Kong, Apr. 2003.
Anderson, S.E., et al., Department of Organismal Biology and Anatomy, University of Chicago, Automatic Recognition and Analysis of Birdsong Syllables from Continuous Recordings, Mar. 8, 1995.
Kogan, Joseph A. and Margoliash, Automated Recognition of bird song elements from continuous recordings using dynamic time warping and hidden Markov models: A Comparative Study, J. Acoust. Soc. Am. (4), Apr. 1998.

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