I am doing a personal project for educational purpose to learn Keras and machine learning. For start, I would like to classify if a sound is a clap or stomp.
I am using a microcontroller that is sound triggered and samples sound @ 20usec. And the microcontroller will send this raw ADC data to the PC for Python processing. I am currently taking 1000 points and get the FFT using numpy (using rfft and getting its absolute value).
Now, I would like to feed the captured FFT signals for clap or stomp as a training data to classify them using neural network. I had been researching for the whole day regarding this and some articles say the Convolutional Neural Network should be used and some say Recurrent Neural Network should be used.
I looked at Convolutional Neural Network and it raised another question, if I should be using Keras' 1-D or 2-D Conv.