Birds Voice Classification using ResNet
Tejashri Manohar Mhatre,  Srijita Bhattacharjee
An area of interest in environment is monitoring animal populations to better understand their behavior, biodiversity, and population dynamics. Audible animals can be automatically classified by their sounds, and a specifically applicative environmental designator is the bird, as it responds quickly to changes in its environment. The aim of this study is to improve accuracy of bird species classifier by using deep residual network, which is implemented and used as a baseline. Literature survey is done on the traditional audio recognition techniques by various researchers in field of deep learning and others. This has not only brought the challenges of understanding the issues in every step of recognition as well as new advancements to overcome the limitations of the previous technique and make it effortless on the user end.
Keywords- Accuracy, Deep Residual Network, Recognition
Cite this Article
Tejashri Manohar Mhatre,  Srijita Bhattacharjee,   "Birds Voice Classification using ResNet"
, International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.6, Issue 4, pp.168-172, November 2018, Available at :http://www.ijedr.org/papers/IJEDR1804032.pdf