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Title: A self-learning audio player that uses a rough set and neural net hybrid approach
Authors: Zuo, Hongming
Keywords: self learning;Artificial Neural Network;music;NN
Issue Date: 16-Oct-2013
Publisher: Laurentian University of Sudbury
Abstract: A self-­‐learning Audio Player was built to learn users habits by analyzing operations the user does when listening to music. The self-­‐learning component is intended to provide a better music experience for the user by generating a special playlist based on the prediction of users favorite songs. The rough set core characteristics are used throughout the learning process to capture the dynamics of changing user interactions with the audio player. The engine is evaluated by simulation data. The simulation process ensures the data contain specific predetermined patterns. Evaluation results show the predictive power and stability of the hybrid engine for learning a users habits and the increased intelligence achieved by combining rough sets and NN when compared with using NN by itself.
Appears in Collections:Computational Sciences - Master's theses
Master's Theses

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