Neural Networks for Automatic Environmental Sound Recognition

Abstract

Environmental sound recognition is currently an important and valuable field of computer science and robotics, security or environmental protection. The underlying methodology evolved from primary speech application characteristic methods to more specific approaches, and with the advent of the deep learning paradigm many attempts using these methods arose. The paper reopens the research we have started on the application of the Feed Forward Neural Networks, by exploring several configurations, and introduces the Convolutional Neural Networks in our investigation. The experiments consider three classes of forest specific sounds and meant to detect the chainsaw sounds, vehicle, and genuine forest.