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Audio Explorer

Audio Explorer is a data visualization tool created by Colin Scruggs and Cameron Henkel of Southwestern University for the 2018 VAST Challenge. Audio Explorer was the recipient of the "Excellent Comprehensive Submission" Award from the VAST committee for 2018's Mini Challenge 1.

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This single-page web app was developed as part of our submission to Mini-Challenge 1. The main objectives of the mini-challenge were to:

  1. Characterize patterns of all bird species found in the Boonsong Lekagal Wildlife Preserve over time, and
  2. Determine whether or not the set of bird calls provided by the Kasios Furniture company supports their claim that the Rose-Crested Blue Pipit is "happily living and nesting in the Preserve."

Audio Explorer was built to synthesize the results of our machine-learning experiments and assist us in examining the geospatial data associated with the large dataset of bird calls provided in Mini-Challenge 1.

For a closer look at how we tackled machine learning, Bird Classification.ipynb is included.
(NOTE: the mini-challenge audio data is required to run this Jupyterlab notebook, and is available for download from the links above)

Live Demo

A live demo of Audio Explorer can be found here.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

Install Node.js and Yarn (if haven't already)

Installing

Clone the repository. Open terminal/commmand prompt and cd to root directory of the repo:

cd [repo directory]

Type yarn install to install dependencies:

yarn install

Deployment

To view a development build of Audio Explorer, run:

yarn serve

Alternatively, to create a production build:

yarn build

The web app can then be viewed at http://localhost:8080/

Built With

Authors

Colin Scruggs - Github

Cameron Henkel - Github

License

This project is licensed under the Apache License 2.0 - see the LICENSE.md file for details.

Acknowledgments

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Southwestern University submission to the 2018 VAST Challenge

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