Underwater audio event detection, identification and classification framework (AQUA)
Date
2016-12-22
Authors
Cipli, Gorkem
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
An audio event detection and classification framework (AQUA) is developed for the North Pacific underwater acoustic research community. AQUA has been developed, tested, and verified on Ocean Networks Canada (ONC) hydrophone data. Ocean Networks Canada is an non-governmental organization collecting underwater passive acoustic data. AQUA enables the processing of a large acoustic database that grows at a rate of 5 GB per day. Novel algorithms to overcome challenges such as activity detection in broadband non-Gaussian type noise have achieved accurate and high classification rates. The main AQUA modules are blind activity detector, denoiser and classifier. The AQUA algorithms yield promising classification results with accurate time stamps.
Description
Keywords
Underwater Audio Event Detection, whale classification, Ocean Networks Canada, Underwater denoiser