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A Fuzzy Rules-based Speech/Music Discrimination Approach for Intelligent Audio Coding Over the Internet

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Our work presents a speech/music discrimination approach based on fuzzy rules for selecting the suitable coder required in an intelligent audio coding system. When the same coder is used for both speech and music, is difficult to achieve good audio quality and low bit rates for both types of signals. We propose using a simple feature, called Warped LPC-based Spectral Centroid (WLPC-SC) for speech/music discrimination. In order to select the suitable audio coder for each audio frame, an expert system is proposed. The main advantage of the proposed approach is the low computational cost in both the speech/music discrimination and coder selection stages. It allows its use in real time applications as internet audio streaming.

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