| Name | group-B-audio-analyzer JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | |
| Summary | A Python package for audio analysis and .wav file classification. |
| upload_time | 2023-11-16 21:21:47 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8 |
| license | |
| keywords |
advent of code
captcha
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
Audio analysis
The customer request is to create a tool to denoise audio tracks and
classify them into three classes: human voices, musical instruments, and
others.
To denoise the audio you should not use any ML algorithm but you are
suggested to adopt a specific Wiener filter..
To classify the audio tracks you can perform the audio analysis in the
Fourier Domain (applying FFT to the original signal).
Use visualisation to show the differences among the three classes of audio
tracks.
Once finished with this task, you can compare this classification with the
one obtainable with a Convolution Neural Network (CNN) applied to the
images obtained from padding the audio tracks. (For this step you can take
advantage of PyTorch or Keras).
The data
To structure and test the first class of your audio data analysis
pipeline, the denoiser, a possibility is to use the clean subset of audio
tracks in the Freesound mono audio track dataset, DBR-dataset, first
adding white random noise to each track, and then, trying to remove the
white noise from the signal.
Using the same dataset you can also test your classifier.
Once you have tested the audio analysis pipeline on this dataset, create a
small data set yourself, recording similar audio tracks and paying
attention to the standardization of the input data.
Useful tools
To convert the audio tracks into signals treatable with Scipy you can use
the PyAudio library.
To construct the Wiener filter you can use the Scipy and Numpy libraries.
Raw data
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"author_email": "Agustin Silva <agustinsilva447@gmail.com>, \"Mahtab T. Nejad \" <mahtabnejadt@gmail.com>, Mahdi Rasouli <mahdi.rasouli77@gmail.com>, Paula Oliveri <olicarpa@gmail.com>",
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