||IS21 Migration of mp3 to wav|
|Detailed description|| A large collection of mp3-files (20 Tbytes - 175.000 files) needs to be migrated to wav. Because of the large amount of data we need automatic QA algorithms to ensure that migration went well.
| Scalability Challenge
|| Large amounts of data (20 Tbytes - 175.000 files) - requires both much I/O and CPU for the migration part as well as I/O and CPU for the QA part. Must be carried out on a distributed platform to be realistic.
|Issue champion||Bjarne Andersen (SB)|
| Other interested parties
|Possible Solution approaches||
|Datasets|| mp3 (128kbit) with Danish Radio broadcasts
|Solutions|| SO2 xcorrSound QA audio comparison tool
SO4 Audio mp3 to wav Migration and QA Workflow
|Objectives||This is about scaleability and robustness. 175.000 files need to be migrated and automatically checked content-wise and format-wise|
|Success criteria||We will have a workflow that converts from mp3 to wav. Checks the migrated files for wav-conformance and checks the actual content by comparing the content of the mp3s and the corresponding wavs to ensure that nothing went wrong|
|Automatic measures|| 1. Process 20 files per hour per node
|Manual assessment|| 1. If any of the migrated files does not pass the QA-test they should actually have failed the migration.
|Actual evaluations||links to acutual evaluations of this Issue/Scenario|
|Title||SO4 Audio mp3 to wav Migration and QA Workflow|
|Detailed description|| Informally the workflow is as follows:
SB currently owns a small collection of real audio filer files (digitised cd’s). They are part of the Danish publications that SB preserves. The rest of the Danish cd collection is in WAV. This format has been chosen as the preservation format as this is a raw format, which needs less interpretation or fewer layers of interpretation to be understood by humans and it is also a robust format.
The Danish Radio Broadcast mp3 files from the mp3 (128kbit) with Danish Radio broadcasts dataset are also to be migrated to WAV according to policy. The actual migration will be done using FFmpeg which is one of the SCAPE Action Services recommended tools. The QA will be split into a number of steps. The first step is validation that the migrated file is a correct file in the wanted format. This is done using JHOVE2 to analyse and provide a JHOVE2 property xml file, and next using a Beanshell in Taverna to check that the jhove2 feature “isValid” is true. The second step compares the header information properties of the original and the migrated files to see if they are ‘close enough’. This is done using FFprobe to extract header information and Taverna Beanshells to compare the extracted properties. Another step could be to extract more properties by ‘playing’ the two files.
The third step uses an analysis tool comparing the sound waves. To do this we have to ‘play’ or interpret the mp3 files. Just as a human needs to ‘play’ or interpret the files to hear the sound. A human cannot look at fileA and tell if it is correct or corrupted. We choose a player P and define ‘fileA played on player P’ to be correct. A small randomly chosen subset of files will be played on player P and checked by human ears to be correct making this definition probable. The player used in this workflow is MPG321. Note that MPG321 is an independent implementation of an mp3-decoder – thus independent from FFmpeg, which is used to actually migrate the file. The result of playing fileA on player P (when noone is listening) is a WAV file. The migrated file is already a WAV file, and we can compare the two files using the analysis tool xcorrSound/migrationQA, see SO2 xcorrSound QA audio comparison tool..
All the used tools are wrapped as SCAPE Web Services and Taverna Workflows.
| Solution Champion
||Bolette Jurik (SB)|
| Corresponding Issue(s)
| myExperiment Links
|| The full workflow is MP3 to WAV Migration +QA. The workflow is combined of a number of smaller workflows, that can also be used or combined in other workflows and solutions:
| Tool Registry Links
||The workflow uses the following tools|
|| This Migration and QA solution has been developed as a Taverna workflow using web services. This puts focus on availability rather than scalability. The sparse tests run i February 2012 have also been run through Taverna. TODO IN DIRE NEED OF AN UPDATE!!!
We tested the Mp3 to Wav Migrate Validate Compare Workflow on file P1_1000_1200_890106_001.mp3 from the mp3 (128kbit) with Danish Radio broadcasts testbed dataset. The file is 112 Mbyte and the duration is 2 hours,
2 minutes and 5.23 seconds. The workflow was run from Taverna on a local work station using the web services deployed on the SB iapetus test machine. The total time for the workflow is 2.3 minutes, and the most expensive nested workflow is the
JHove2Validate workflow with 1.3 minutes, closely followed by the FFmpegMigrate workflow with 59.2 s. The FFprobeExtractCompare workflow with 12.9 seconds seems to be the cheaper QA in this set-up. The result of the workflow is a migrated
WAV file, and a report that it is valid and that the extracted properties have been preserved.
Running the workflow on 4 additional files from the dataset gave similar results of between 2.2 and 2.3 minutes, valid migrated WAV files and properties preserved. The 6th test run also gave a result wav file, but we could not hear the file, and neither
JHOVE2 or FFprobe was able to read the file. Interestingly the nested FFprobe workflow failed, while the nested JHove2 workflow finished, but without output. At the intermediate values, we see the JHOVE2 SCAPE web service is unable to read the
migrated file. This raises a question of error handling in the Taverna workflows. The nice feature is that in this layered approach, it is still easy to pinpoint where the error originated, but we may want to look at more consistent error handling. Maybe the
workflow should not fail in this case, but rather give meaningful output about a failed web service or beanshell.
We note that we are working on 2-hour sound files. The average file size of the original mp3 files is only 118Mb, but the migrated wav files are approximately 1.4Gb. This means we can probably not hope to improve much on the performance of the
actual FFmpeg migration of the individual files. The mp3 (128kbit) with Danish Radio broadcasts collection is 20 TB and around 150000 files. This means that running the basic workflow migrations sequentially on the test machine would take around 300
days. We can however hope to improve by using the Scape execution platform instead of doing the migrations sequentially.
The migrationQA workflow was tested separately, see SO2 xcorrSound QA audio comparison tool.
The full MP3 to WAV Migration + QA workflow has been tested on a shorter file using the ONB webservices. The input mp3 file was the Creative Commons example file http://ia700308.us.archive.org/21/items/Radiators2008-09-19/Rads2008-19-09-d1t02_vbr.mp3. The total time was 47.9 seconds. The time for FFmpegMigrate 12.2 seconds. For FFprobeExtractCompare 5.5 seconds. For JHove2Validate 9.6 seconds. And for migrationQA comparison including MPG321 decoding 31 seconds.The output wav file is available from http://fue.onb.ac.at/scape/tmp/Rads2008-19-09-d1t02_vbr.mp3_SCAPEFFMPEG25305Service_wavFile_4413676179244047691.wav. The JHOVE2 validation, the FFprobe comparison and the migrationQA comparison returned true, and the output of the migrationQA comparison looks like this:
The solution performs as expected and solves the corresponding issue,but further testing for accuracy and performance is required.
|Title||SO2 xcorrSound QA audio comparison tool|
|Detailed description|| The xcorrSound QA audio comparison tool compares two sound waves, for instance the audio waves of an original audio file and the audio waves of a migrated file. The tool uses the cross correlation function to find the overlap match. This will give us a match score (between 0 and 1) and also an offset in the second file for the match if the audio has been shifted in the migration (we have examples of this happening). This is not a full solution, but a tool used as part of the workflows in full solutions to a number of issues.
| Solution Champion
||Bolette Jurik (SB)|
| Corresponding Issue(s)
| myExperiment Link
|| migrationQA SCAPE Web Service Wav File Comparison Workflow
| Tool Registry Link
Performance efficiency - Capacity / Time behaviour
The testbed dataset Danish Radio broadcasts, mp3 which is the basis of issue IS21 Migration of mp3 to wav consists of two hour mp3 files (average file size: 118Mb). When these two hour files are migrated to WAV, we get an average file size around 1.4Gb. In February 2012 the migrationQA workflow did not scale nicely to these two hour sound files, but we have run a test on a file cut to 12Mb (about a tenth of the original size) using dd. The Mp3 to Wav Migrate Validate Compare Workflow (see SO4 Audio mp3 to wav Migration and QA Workflow) used only 34 seconds on the cut file. The migration and the file format validation were successful, but the property comparison reported that the files were not 'close enough'. The reason for this is that cutting the file does not change the header information, so the duration of the original cut file is supposedly 2 hours, 2 minutes and 5.23 seconds, while the duration of the migrated file is 13 minutes and 6.38 seconds. Playing the original cut mp3 using the MPG321 Play mp3 to Wav SCAPE Web Service Workflow (see SO4 Audio mp3 to wav Migration and QA Workflow) used 11.7 seconds. The migrationQA SCAPE Web Service Wav File Comparison Workflow took 1.4 minutes. The result was also negative, but an inspection of the output showed that only the last chunk differed, which probably means that FFmpeg and MPG321 handled the cut off differently.