ISSS608 2017-18 T3 Assign Zhang Yingdi Task2

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Images.jpg VAST Mini Challenge 1: "Cheep" Shots?

Background

Methodology

Task 1

Task 2

Conclusions

 


Kasios are reporting that there are plenty of Rose-crested Blue Pipits happily living and nesting in the Preserve. They have provided a set of Pipit bird calls, recently recorded across the Preserve, with locations of where they were recorded. They claimed the Rose-crested Blue Pipits are a thriving population. The objective of this question is to investigate if the claim by Kasios are factual. To support the investigation, both Machine Learning approach and Visualization Approach are applied. This question is mainly explored in R and Tableau.

Data Preparation

R is used for the data preparation. The audio files in the “ALL BIRDS” folder will be used to train and test the model. The audio files in the “Test Birds from Kasios” folder will be used to predict the outcome. For the Machine Learning approach, a classifier will be built to predict if the given 15 test audio files are Pipit bird calls.

All the audio files are given in MP3 format. To analyse the audio files, firstly, the MP3 files are converted to .wav format using wirteWav() function. Next, convert the .wav files to data frame using the analyzeFolder() function. Due to the long-time of processing large number of files, only audio files with quality “A” in “ALL BIRDS” folder is selected to be used in this question. The result of the analyzeFolder() for audio files in “ALL BIRDS” folder and “Test Birds from Kasios” folder are saved as “all_birds_wav.csv” and “test_birds_from_kasios_wav.csv” respectively.

The converted .csv files contains 72 columns shown as below:


Task1-15-.png


Column sound is the .wav files name. The rest columns are all parameters of the audio files with numeric values.