Designing and training a NN model
In this recipe, we will be leveraging the following NN architecture to recognize our words:
Figure 4.20 – NN architecture
The model has two two-dimensional (2D) convolution layers, one dropout layer, and one fully connected layer, followed by a softmax activation.
The network's input is the MFCC feature extracted from the 1-s audio sample.
Getting ready
To get ready for this recipe, we just need to know how to design and train a NN in Edge Impulse.
Depending on the learning block chosen, Edge Impulse exploits different underlying ML frameworks for training. For a classification learning block, the framework uses TensorFlow with Keras. The model design can be performed in two ways:
- Visual mode (simple mode): This is the quickest way and through the user interface (UI). Edge Impulse provides some basic NN building blocks and architecture presets, which are beneficial if you have just started experimenting...
