Building a deep learning audio event identifier

We will now look at a strategy using which we can build an actual audio event identifier by leveraging the classification model we built in the previous section. This will enable us to take any new audio file and predict which category it might belong to by making use of the entire workflow we defined in this chapter, starting from building the base feature maps, extracting features using the VGG-16 model, and then leveraging our classification model to make a prediction. The code snippets used in this section are also available in the Prediction Pipeline.ipynb Jupyter Notebook in case you want to run the examples yourself. The Notebook contains the AudioIdentifier class, which we have created by reusing all the components we have built in the previous sections of this chapter. Do refer to the Notebook to access the full code for this class as we will be focusing more on the actual prediction pipeline to keep the content more concise. We will...