This thesis sets out to implement an extended feedback delay network with a comprehensive set of parameters that can be estimated by a proposed neural network. The goal of the neural network is to use audio differentiation to tune the parameters of the feedback delay network, to allow it to emulate other reverberators. The feedback delay network is implemented as a VST3 audio plugin and embedded in the neural network via a proposed audio processing model. Qualitative evaluation is done on the performance of the plugin and the neural network, and a perceptual listening test is done to evaluate the subjective quality of the reverberated signals created by the estimated reverberation parameters.