jsingh811 / pyaudioprocessing Goto Github PK
View Code? Open in Web Editor NEWAudio feature extraction and classification
License: GNU General Public License v3.0
Audio feature extraction and classification
License: GNU General Public License v3.0
The gfcc feature can be optimized in terms of computations and scale. This ticket entails work for the betterment of gfcc feature calculation.
Add audio cleaning methods to remove low-activity regions.
Add audio visualization wrappers.
Currently, classifier stats for different hyper-parameters and the final confusion matrix prints to the screen. We want to add functionality that also saves the output to disc and displays it is easy to understand visualizations(ideas welcome!).
-[ ] Shortlist visualization tools
-[ ] Implement and integrate the tool selected after review
Due to actions/setup-python#544, workflows for Python 3.6 aren't working at this time on latest Ubuntu versions. Once there is a resolution, add Python 3.6 to the workflows.
Add a pytest script to test functions inside features
dir.
-[ ] Add unit tests for functions in features
The ability to convert audio files from mp4, mp3, mp4 or aac to wav.
Add pytest script to test functions written in run_classifications.py.
-[ ] Add unit tests for functions in run_classifications.py
##Description
A mel spectrogram is a spectrogram where the frequencies are converted to the mel scale.
The images of mel-spectrograms are widely used with CNNs to classify audio.
There are two classes in the model, if one has a score of 0.1, surely the other has a score of 0.9? How to modify it to judge the classification one by one?
Currently, mfcc and gfcc features are being computed as a mid step of a classification problem and we don't get a direct view of the features.
One can want to look at these features independently and use them with a different classification backend.
% codespell --ignore-words-list="fo" --quiet-level=2
./pyAudioProcessing/extract_features.py:74: stucture ==> structure
./pyAudioProcessing/trainer/audioTrainTest.py:49: containt ==> contain, content
./pyAudioProcessing/trainer/audioTrainTest.py:68: containt ==> contain, content
./pyAudioProcessing/trainer/audioTrainTest.py:242: signle ==> single
./pyAudioProcessing/trainer/audioTrainTest.py:242: seperate ==> separate
./pyAudioProcessing/features/audioFeatureExtraction.py:255: seperate ==> separate
./pyAudioProcessing/features/filters.py:122: eigth ==> eighth, eight
./pyAudioProcessing/features/filters.py:123: eigth ==> eighth, eight
Undefined name discovered by #3 https://github.com/jsingh811/pyAudioProcessing/search?q=beatExtraction
Install not working on linux - unfulfilled dependency python-magic-bin==0.4.14
detail: Centos 8
Clone repo git clone https://github.com/jsingh811/pyAudioProcessing.git
install with pip3 install -e .
Failed dependency
Downloading https://files.pythonhosted.org/packages/79/db/eaf620b73a1eec3c8c6f8f5b0b236a50f9da88ad57802154b7ba7664d0b8/pydub-0.23.1-py2.py3-none-any.whl
Collecting python-magic-bin==0.4.14 (from pyAudioProcessing==1.1.6)
Could not find a version that satisfies the requirement python-magic-bin==0.4.14 (from pyAudioProcessing==1.1.6) (from versions: )
No matching distribution found for python-magic-bin==0.4.14 (from pyAudioProcessing==1.1.6)
Reviewing python-magic-bin, I don't see a linux version.
Can you advise?
Currently we can't isolate features from classifications. This feature attempts to isolate the two processes so each can be performed independent of the other.
Add a pytest script to test functions inside trainer.
-[ ] Add unit tests for functions in trainer
Add a pytest script to test functions inside extract_features.py.
-[ ] Add unit tests for functions in extract_features.py
LPC and LPCC feature integration.
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