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B2P2: A scalable big bioacoustic processing platform


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

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Copyright 2016 IEEE

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


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 and systems software
Research Field:Distributed systems and algorithms
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Thudumu, S (Mr Srikanth Thudumu)
UTAS Author:Garg, S (Dr Saurabh Garg)
UTAS Author:Montgomery, J (Dr James Montgomery)
ID Code:111792
Year Published:2016
Deposited By:Information and Communication Technology
Deposited On:2016-10-07
Last Modified:2018-01-18
Downloads:9 View Download Statistics

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