Troubleshooting & Batch Processing
Starting: 8th July 2019 – 8/7/19
Goal For this week was to finish extracting the .wav files from the .mat files and batch convolving code.
Emailed the people at Aachen University for the .wav file version of the IRs, not in the .mat files, however they were 24bit files which wavefile.read() doesn’t work with. (ref:https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.wavfile.read.html)
I realised that the audio distortion problem from last week was only happening when the data was being exported as a .wav. This was fixed by changing the export function I was using to the scipy.io wavfile.write() function.
As such I managed to extract the IRs from the MAT Files as 2channel, 64bit, 48000hz .wav files. This also meant I was able to export the convolved files.
Batch Convolving and Exporting
Wrote a program that could batch convolve a folder of wav files with an IR.
Realised some files didn’t work with the convolution because they were stereo and the IRs were Mono, to solve I wrote a script to check the number of channels on each file and Convert them to mono if they were stereo.
Also Realised that when convolving some files could get too loud or quiet so I wrote a function to normalise all the output wav files between -0.8 & 0.8 so they don’t clip and distort.
Finished batch convolver program and gave it a naming function that would combine the IR and Name of the Dry Wav file.
Ran it over night and generated about 10GB of convolved and labeled files to begin training the first round of Neural Nets.
Plan for next week is to spray data to a cluster and begin processing the data with ECL