Spectrogram is hazy and hard to distinguish patterns

[yusufkhanmohammad]

spectrogram.ipynb uses soundfile library and makes a spectrogram a bit hazy, tried doing with Librosa amplitude_to_db spectrogram AtoD = librosa.amplitude_to_db(np.abs(librosa.stft(data)), ref=np.max)

https://colab.research.google.com/drive/1LRdUcsKTiBI-ERVJQ0OEImcUo7WqtjrN

[veirs]

Mohammad, I suggest you try to make a spectrogram from just the first file in the flac directory. This first call we term S 1 and is the most common call that the local orca use. It should give you a spectrogram similar to the one below I just made with Audacity from that first file. Val [image: image.png]

On Wed, Mar 18, 2020 at 12:00 PM Mohammad Yusuf Khan < notifications@github.com> wrote:

spectrogram.ipynb uses soundfile library and makes a spectrogram a bit hazy, tried doing with Librosa amplitude_to_db spectrogram AtoD = librosa.amplitude_to_db(np.abs(librosa.stft(data)), ref=np.max)

https://colab.research.google.com/drive/1LRdUcsKTiBI-ERVJQ0OEImcUo7WqtjrN

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[atreyamaj]

Hey, a good way to start enhancing the spectrogram would be to remove noise from the audio signal before computing the spectrogram (maybe using a package like open-unmix-pytorch). Some possible ways to enhance the spectrogram are:

1. band pass filtering
2. spectral subtraction
3. using a wiener filter
4. wavelet packet decomposition

More information can be found in this interesting research paper: http://aircconline.com/sipij/V3N2/3212sipij01.pdf

[kunakl07]

Interesting paper @atreyamaj Here is the first stage of preprocessing that I performed on S_1 .wav file. I think this notebook will help to get a basic look of preprocessing https://colab.research.google.com/drive/1ckW8EaIO9Vf1n4KZHz289aryWKrclHtF

[atreyamaj]

This notebook is great! Thanks for sharing it @kunakl07 , I'm sure it'll help others looking to preprocess data too!

[kunakl07]

Welcome @atreyamaj , the actual credits go to Abhishek Singh and Jesse Lopez who performed these preprocessing tasks. I have used it to apply on S_1.wav file which is here.

[atreyamaj]

@yusufkhanmohammad Hey, I just came across a python library that can be used for denoising. The detailed steps for how it does so are given in the documentation. Link: https://pypi.org/project/noisereduce/