Developing an Audio QA workflow using Hadoop: Part II
First things first. The Github repository with the Audio QA workflows is here: https://github.com/statsbiblioteket/scape-audio-qa. And version 1 is working. Version is really all wrong here. I should call it Workflow 1, which is this one:
To sum up what this workflow does, is migration, conversion and content comparison. The top left box (nested workflow) migrates a list of mp3s to wav files using a Hadoop map-reduce job using the command line tool Ffmpeg, and outputs a list of migrated wav files. The top right box converts the same list of mp3s to wav files using another Hadoop map-reduce job using the command line tool mpg321, and outputs a list of converted wav files. The Taverna work flow then puts the two lists of wav files together and the bottom box receives a list of pairs of wav files to compare. The bottom box compares the content of the paired files using a Hadoop map-reduce job using the xcorrSound waveform-compare commandline tool, and outputs the results of the comparisons.
What we would like to do next is:
- "Reduce" the output of the Hadoop map-reduce job using the waveform-compare commandline tool
- Do an experiment on 1TB input mp3 files on the SB Hadoop cluster, and write an evaluation and a new blog post 😉
- Extend the workflow with property comparison. The waveform-compare tool only compares sound waves; it does not look at the header information. This should be part of a quality assurance of a migration. The reason this is not top priority is that FFprobe property extraction and comparison is very fast, and will probably not affect performance much…
By BoletteJurik, posted in BoletteJurik's Blog
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