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B2P2: A scalable big bioacoustic processing platform

Citation

Thudumu, S and Garg, S and Montgomery, J, B2P2: A scalable big bioacoustic processing platform, Proceedings of IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science, 12-14 December 2016, Sydney, Australia, pp. 1211-1217. ISBN 978-1-5090-4297-5 (2016) [Refereed Conference Paper]

Copyright Statement

Copyright 2016 IEEE

Official URL: http://dx.doi.org/10.1109/HPCC-SmartCity-DSS.2016....

DOI: doi:10.1109/HPCC-SmartCity-DSS.2016.74

Abstract

Many application areas such as biodiversity monitoring and speech recognition produce several gigabytes of audio data per day; think of weeks, months of accumulated data available to analyse. However, current methods and frameworks can only process a few megabytes at a time. Moreover, these methods require a lot of manual processing before they can give relevant results for biodiversity researchers. In this paper, we present a novel scalable framework called B2P2 for handling large audio files and processing them in an efficient manner. The proposed framework can process and handle large audio data that can indicate whether there are sounds of potential interest throughout large audio recordings. We implemented the proposed framework using BigData platforms such as Spark and HDFS. Experimental results demonstrate an increase in speed-up and performance of processing audio files when increasing nodes and data sizes on cloud computing.

Item Details

Item Type:Refereed Conference Paper
Keywords:big data, cloud computing
Research Division:Information and Computing Sciences
Research Group:Distributed Computing
Research Field:Distributed and Grid Systems
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Application Tools and System Utilities
Author:Thudumu, S (Mr Srikanth Thudumu)
Author:Garg, S (Dr Saurabh Garg)
Author:Montgomery, J (Dr James Montgomery)
ID Code:111792
Year Published:2016
Deposited By:Computing and Information Systems
Deposited On:2016-10-07
Last Modified:2017-06-21
Downloads:9 View Download Statistics

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