摘要
A good voice-band signal classification can not only enable the safe application of speech ceding techniques, the implementation of a Digital Signal Interpolation （DSI） system, but also facilitate network administration and planning by providing accurate voice-band traffic analysis. A new method is proposed to detect and classify the presence of various voice-band signals on the General Switched Telephone Network （GSTN）. The method uses a combination of simple base classifiers through the AdaBoost algorithm. The conventional classification features for voice- band data classification are combined and optimized by the AdaBoost algorithm and spectral subtraction method. Experiments show the simpleness, effectiveness, efficiency and flexibility of the method.
A good voice-band signal classification can not only enable the safe application of speech coding techniques, the implementation of a Digital Signal Interpolation (DSI) system, but also facilitate network administration and planning by providing accurate voice-band traffic analysis. A new method is proposed to detect and classify the presence of various voice-band signals on the General Switched Telephone Network (GSTN). The method uses a combination of simple base classifiers through the AdaBoost algorithm. The conventional classification features for voice-band data classification are combined and optimized by the AdaBoost algorithm and spectral subtraction method. Experiments show the simpleness, effectiveness, efficiency and flexibility of the method.
