Efficient wavelet-based voice/data discriminator for telephone networks
Patrick J. Quirk, Yi-Chyun Tseng, Reza R. Adhami · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
A broad array of applications in the Public Switched Telephone Network (PSTN) require detailed information about type of call being carried. This information can be used to enhance service, diagnose transmission impairments, and increase available call capacity. The increase in data rates of modems and the increased usage of speech compression in the PSTN has rendered existing detection algorithms obsolete. Wavelets, specifically the Discrete Wavelet Transform (DWT), are a relatively new analysis tool in Digital Signal Processing. The DWT has been applied to signal processing problems ranging from speech compression to astrophysics. In this paper, we present a wavelet-based method of categorizing telephony traffic by call type. Calls are categorized as Voice or Data. Data calls, primarily modem and fax transmissions, are further divided by the International Telecommunications Union-Telephony (ITU-T), formerly CCITT, V-series designations (V.22bis, V.32, V.32bis, and V.34).