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There is significant interest in the audio community in developing web-based applications using HTML5 and Web Audio API. Whilst this newly emerging API goes some way to provide offline audio analysis in the web browser it is limited to a relatively basic FFT with fixed Blackman windowing and no overlap facility. Most previously documented solutions to this issue operate in real time. This paper demonstrates how to perform more sophisticated, faster than real time FFT analysis for use within Web Audio applications. It makes use of the Web Audio API and the dsp.js library. Academics and researchers can use this paper as a tutorial to develop similar solutions within their own web based audio applications.
Author (s): Joglar-Ongay, Luis; Dewey, Christopher; Wakefield, Jonathan
Affiliation:
University of Huddersfield, Huddersfield, West Yorkshire, UK
(See document for exact affiliation information.)
AES Convention: 140
Paper Number:242
Publication Date:
2016-05-06
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Session subject:
eBriefs: Posters
Permalink: https://aes2.org/publications/elibrary-page/?id=18146
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Joglar-Ongay, Luis; Dewey, Christopher; Wakefield, Jonathan; 2016; Implementation of Faster than Real Time Audio Analysis for Use with Web Audio API: An FFT Case Study [PDF]; University of Huddersfield, Huddersfield, West Yorkshire, UK; Paper 242; Available from: https://aes2.org/publications/elibrary-page/?id=18146
Joglar-Ongay, Luis; Dewey, Christopher; Wakefield, Jonathan; Implementation of Faster than Real Time Audio Analysis for Use with Web Audio API: An FFT Case Study [PDF]; University of Huddersfield, Huddersfield, West Yorkshire, UK; Paper 242; 2016 Available: https://aes2.org/publications/elibrary-page/?id=18146
@article{joglar-ongay2016implementation,
author={joglar-ongay luis and dewey christopher and wakefield jonathan},
journal={journal of the audio engineering society},
title={implementation of faster than real time audio analysis for use with web audio api: an fft case study},
year={2016},
number={242},
month={may},}