Question/Issue:
I used spectrogram as processing block in my create impulse section. While performing classification i can see it is using 1,287 features as input to my DNN model. How to know what are the names of these features that it is considering?
Project ID:
420678
Hello @yogeshwar_t,
The spectrogram block first divides the window in multiple overlapping frames. The size and number of frames can be adjusted with the parameters Frame length and Frame stride. For example with a window of 1 second, frame length of 0.02s and stride of 0.01s, it will create 99 time frames.
An FFT is then calculated for each frame. The number of frequency features for each frame is equal to the FFT size parameter divided by 2 plus 1. We recommend keeping the FFT size a power of 2 for performances purpose. Finally the Noise floor value is applied to the power spectrum.
The features generated by the Spectrogram block are equal to the number of generated time frames times the number of frequency features.
Here is the spectrogram block documentation page: Spectrogram | Documentation
And the associated code: processing-blocks/spectrogram/dsp.py at master · edgeimpulse/processing-blocks · GitHub
I hope this helps.
Best,
Louis