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Proceedings Paper

Efficient wavelet-based voice/data discriminator for telephone networks
Author(s): Patrick J. Quirk; Yi-Chyun Tseng; Reza R. Adhami
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Paper Abstract

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).

Paper Details

Date Published: 7 June 1996
PDF: 8 pages
Proc. SPIE 2750, Digital Signal Processing Technology, (7 June 1996); doi: 10.1117/12.241983
Show Author Affiliations
Patrick J. Quirk, Sierra Semiconductor (United States)
Yi-Chyun Tseng, DSC Communications Corp. (United States)
Reza R. Adhami, Univ. of Alabama in Huntsville (United States)


Published in SPIE Proceedings Vol. 2750:
Digital Signal Processing Technology
Joseph Picone, Editor(s)

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