Difference between revisions of "ISSS608 2017-18 T3 Assign Wang Runyu Data Preparation"
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==Data Cleaning== | ==Data Cleaning== | ||
Text file AllBirdsV4.csv's format contains inconsistent data fields and missing data. | Text file AllBirdsV4.csv's format contains inconsistent data fields and missing data. | ||
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1. Format Date Field to MM/DD/YYYY. | 1. Format Date Field to MM/DD/YYYY. | ||
Revision as of 23:19, 6 July 2018
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Data Description
all birds audio files
test bird audio files
audio bird text file
test bird text file
Data Cleaning
Text file AllBirdsV4.csv's format contains inconsistent data fields and missing data.
1. Format Date Field to MM/DD/YYYY.
2. Omit data with no date value. As date field is important for us to identify the existent of certain bird specie.
3. Recode the time to 24 hour scale with format hh:mm. Recode empty time to 12:00, early morning to 8:00.
Audio File Processing
1. To process the audio files, following R packages are loaded in this assignment: soundgen, tuneR, seewave
2. As the function analyzeFolder() which converts audio files to dataframe can only read WAV format, it is necessary for me to convert MP3 format to WAV format. In the first step, I convert the all the MP3 audio files to WAV format
3. Not all the audio files are good quality. Some audio contains noise which will distract the audio classification task. Extract all the audio files which quality is A
4. Call analyzeFolder() to read all the wav file as dataframe. And store the dataframe as csv format. Audio files in both All Birds and Test Birds from Kasios are required to process as above
The actual code can be found at here