timate the requirement would be at least 100 times more pixels as well as additional circuits that mimic the movement-sensitive and edge-enhancing functions of the eye. They feel it is possible to achieve this number of pixels in the near future. When it does arrive, the new technology will likely be capable of recognizing human faces. Visual recognition would have an undeniable effect on reducing crime in automated financial transactions. Future technology breakthroughs will bring visual recognition closer to the recognition of individuals, thereby enhancing the security of automated financial transactions. Computer-Aided Voice Recognition Voice recognition is another area that has been the subject of neural network research. Researchers have long been interested in developing an accurate computer-based system capable of understanding human speech as well as accurately identifying one speaker from another. Current Research Ben Yuhas, a computer engineer at John Hopkins University, has developed a promising system for understanding speech and identifying voices that utilizes the power of neural networks. Previous attempts at this task have yielded systems that are capable of recognizing up to 10,000 words, but only when each word is spoken slowly in an otherwise silent setting. This type of system is easily confused by back ground noise (Moyne 100). Ben Yuhas' theory is based on the notion that understanding human speech is aided, to some small degree, by reading lips while trying to listen. The emphasis on lip reading is thought to increase as the surrounding noise levels increase. This theory has been applied to speech recognition by adding a system that allows the computer to view the speakers lips through a video analysis system while hearing the speech. The computer, through the neural network, can learn from its mistakes through a training session. Looking ...
