Fast Detection of Specific Information in Voice Signal over Internet Protocol

The world Telecommunications industry caters to both Wireline and Wireless business. In the present Fourth Generation (4G) wireless world rapid change is the only constant factor. The biggest paradigm change being the move from Circuit Switched to Packet Switched technologies. Voice over Packet (VoP) is transforming telephony by rapidly replacing the legacy circuit-switched technology. The VoP technology unites the telephony and data worlds allowing voice, facsimile, and video traffics to be relayed over managed IP networks or corporate intranets around the world. In this paper, various aspects of Voice over Internet Protocol (VoIP) are discussed, including the architecture for the NGMN, challenges, standards and the application areas. In addition a new approach for fast detecting certain information in VOIP is presented. The entire data are collected together in a long vector and then tested as a one input pattern. Proposed fast time delay neural networks (FTDNNs) use cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented time delay neural networks is less than that needed by conventional time delay neural networks (CTDNNs). Simulation results using MATLAB confirm the theoretical computations.