Visualization of audio records for automatic bird species identification

This paper presents a new visual analytic mechanism to allow ornithologists to analyze large collections of audio signals for automatic bird species identification. The proposed mechanism is based on audio signal processing, machine learning and visualization techniques. A collection of Colombian birds audio records is used to build a visualization that allows to visually analyze bird species. Results show that the proposed method is promising to facilitate the identification of bird species.

[1]  Luc Lens,et al.  Evidence for organism-wide asymmetry in five bird species of a fragmented afrotropical forest , 1999, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[2]  Jinhai Cai,et al.  Sensor Network for the Monitoring of Ecosystem: Bird Species Recognition , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.

[3]  Hervé Glotin,et al.  LifeCLEF 2014: Multimedia Life Species Identification Challenges , 2014, CLEF.

[4]  Fabio A. González,et al.  Multimodal visualization based on latent topic analysis , 2014, 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW).

[5]  Trevor Darrell,et al.  DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition , 2013, ICML.

[6]  J. Tenenbaum,et al.  A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.

[7]  W. Torgerson Multidimensional scaling: I. Theory and method , 1952 .

[8]  Paul Roe,et al.  A toolbox for animal call recognition , 2012 .

[9]  Jorge Camargo,et al.  Visualizing multimodal image collections , 2013, Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013.

[10]  Michael C. Hout,et al.  Multidimensional Scaling , 2003, Encyclopedic Dictionary of Archaeology.

[11]  Ian T. Jolliffe,et al.  Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.

[12]  Steve Kelling,et al.  BirdVis: Visualizing and Understanding Bird Populations , 2011, IEEE Transactions on Visualization and Computer Graphics.

[13]  Y. Takane,et al.  Multidimensional Scaling I , 2015 .

[14]  Brian D. Fisher,et al.  Towards the Personal Equation of Interaction: The impact of personality factors on visual analytics interface interaction , 2010, 2010 IEEE Symposium on Visual Analytics Science and Technology.

[15]  Nascif A. Abousalh-Neto,et al.  Big data exploration through visual analytics , 2012, IEEE VAST.

[16]  Xiaoli Z. Fern,et al.  Acoustic classification of multiple simultaneous bird species: a multi-instance multi-label approach. , 2012, The Journal of the Acoustical Society of America.

[17]  Hervé Glotin,et al.  Clusterized Mel Filter Cepstral Coefficients and Support Vector Machines for Bird Song Identification , 2014 .