APM Quality Assessment tool
Python wrapper of APM simulators (e.g., audioproc_f) with which quality
assessment can be automatized. The tool allows to simulate different noise
conditions, input signals, APM configurations and it computes different scores.
Once the scores are computed, the results can be easily exported to an HTML page
which allows to listen to the APM input and output signals and also the
reference one used for evaluation.
Dependencies
- OS: Linux
- Python 2.7
- Python libraries: enum34, numpy, scipy, pydub (0.17.0+), pandas (0.20.1+), pyquery (1.2+), jsmin (2.2+), csscompressor (0.9.4)
- It is recommended that a dedicated Python environment is used
- install
virtualenv $ sudo apt-get install python-virtualenv- setup a new Python environment (e.g.,
my_env) $ cd ~ && virtualenv my_env- activate the new Python environment
$ source ~/my_env/bin/activate- add dependcies via
pip (my_env)$ pip install enum34 numpy pydub scipy pandas pyquery jsmin \csscompressor
- install
- PolqaOem64 (see http://www.polqa.info/)
- Tested with POLQA Library v1.180 / P863 v2.400
- Aachen Impulse Response (AIR) Database
- Input probing signals and noise tracks (you can make your own dataset - *1)
Build
- Compile WebRTC
- Go to
out/Default/py_quality_assessmentand check thatapm_quality_assessment.pyexists
Unit tests
- Compile WebRTC
- Go to
out/Default/py_quality_assessment - Run
python -m unittest discover -p "*_unittest.py"
First time setup
- Deploy PolqaOem64 and set the
POLQA_PATHenvironment variable- e.g.,
$ export POLQA_PATH=/var/opt/PolqaOem64
- e.g.,
- Deploy the AIR Database and set the
AECHEN_IR_DATABASE_PATHenvironment variable- e.g.,
$ export AECHEN_IR_DATABASE_PATH=/var/opt/AIR_1_4
- e.g.,
- Deploy probing signal tracks into
out/Default/py_quality_assessment/probing_signals(*1)
- Deploy noise tracks into
out/Default/py_quality_assessment/noise_tracks(*1, *2)
(*1) You can use custom files as long as they are mono tracks sampled at 48kHz encoded in the 16 bit signed format (it is recommended that the tracks are converted and exported with Audacity).
Usage (scores computation)
- Go to
out/Default/py_quality_assessment - Check the
apm_quality_assessment.shas an example script to parallelize the experiments - Adjust the script according to your preferences (e.g., output path)
- Run
apm_quality_assessment.sh - The script will end by opening the browser and showing ALL the computed scores
Usage (export reports)
Showing all the results at once can be confusing. You therefore may want to
export separate reports. In this case, you can use the
apm_quality_assessment_export.py script as follows:
- Set
--output_dir, -oto the same value used inapm_quality_assessment.sh - Use regular expressions to select/filter out scores by
- APM configurations:
--config_names, -c - capture signals:
--capture_names, -i - render signals:
--render_names, -r - echo simulator:
--echo_simulator_names, -e - test data generators:
--test_data_generators, -t - scores:
--eval_scores, -s
- APM configurations:
- Assign a suffix to the report name using
-f <suffix>
For instance:
$ ./apm_quality_assessment_export.py \
-o output/ \
-c "(^default$)|(.*AE.*)" \
-t \(white_noise\) \
-s \(polqa\) \
-f echo
Usage (boxplot)
After generating stats, it can help to visualize how a score depends on a
certain APM simulator parameter. The apm_quality_assessment_boxplot.py script
helps with that, producing plots similar to this
one.
Suppose some scores come from running the APM simulator audioproc_f with
or without the level controller: --lc=1 or --lc=0. Then two boxplots
side by side can be generated with
$ ./apm_quality_assessment_boxplot.py \
-o /path/to/output
-v <score_name>
-n /path/to/dir/with/apm_configs
-z lc
Troubleshooting
The input wav file must be:
- sampled at a sample rate that is a multiple of 100 (required by POLQA)
- in the 16 bit format (required by
audioproc_f) - encoded in the Microsoft WAV signed 16 bit PCM format (Audacity default when exporting)
Depending on the license, the POLQA tool may take “breaks” as a way to limit the throughput. When this happens, the APM Quality Assessment tool is slowed down. For more details about this limitation, check Section 10.9.1 in the POLQA manual v.1.18.
In case of issues with the POLQA score computation, check
py_quality_assessment/eval_scores.py and adapt
PolqaScore._parse_output_file().
The code can be also fixed directly into the build directory (namely,
out/Default/py_quality_assessment/eval_scores.py).