Neural Networks

This approach focused primarily on multilayer perceptrons the categorize the bird calls. This type of network consists of two major components, axons and synapses. The axons contain a number of neurons, and apply a discriminating function to any signal. These axons are connected to each other by synapses. Each synapse connects a single neuron in one axon to a neuron in another axon. When the first axon transmits a signal through the specific neuron, the synapse scales the signal by its weigh, which may be positive (excitory) or negative (inhibitory), before passing it to the next neuron. By connecting several axons together in this manner, a non-linear transfer function can be applied to a set of input data.

The key to a neural network comes in its training. When a set of data is input to the network, the resulting values can be retrieved and compared to the desired value. Then the difference in the values can be propagated backwards through the network by applying the inverse of the discriminatory functions and synaptic weights. The synaptic weights are then changed to bring them slightly closer to the weights required to produce the desired results. The training of the network is achieved in this way with a large amount of data and many iterations through the data (epochs). With a sufficient number of epochs, the synaptic weights can approach values that will correctly categorize a variety of different input signals.

A variety of data sets were used as described above. It was found that due to the time variance of the signals, the longer interval lengths tended to provide much better results. As a result, the interval parameter was removed from consideration, and the entire vocalization was analyzed as one interval. The simplicity of this approach encapsulated all of the characteristics of the vocalizations in a compact form thus reducing the processing time dramatically.

It was decided that the dominant frequency of each call was an important characteristic of the vocalization.

There were four different styles of network built. The first was built to distinguish between the House and Purple Finches. The second was trained and tested on four species in the Empidomax genus of Flycatcher. The third investigated the networks response to song mimickery. The final network was built to accommodate a larger number of bird species.


Classification 1: House and Purple Finches

Classification 2: Empidonax Flycatchers

Classification 3: Mimickery

Classification 4: Many Species Classification