at silent video stills of people saying each individual vowel, the network developed a series of images of the different mouth, lip, teeth, and tongue positions. It then compared the video images with the possible sound frequencies and guessed which combination was best. Yuhas then combined the video recognition with the speech recognition systems and input a video frame along with speech that had background noise. The system then estimated the possible sound frequencies from the video and combined the estimates with the actual sound signals. After about 500 trial runs the system was as proficient as a human looking at the same video sequences. This combination of speech recognition and video imaging substantially increases the security factor by not only recognizing a large vocabulary, but also by identifying the individual customer using the system. Current Applications Laboratory advances like Ben Yuhas have already created a steadily increasing market in speech recognition. Speech recognition products are expected to break the billion-dollar sales mark this year for the first time. Only three years ago, speech recognition products sold less than $200 million (Shaffer, 238). Systems currently on the market include voice-activated dialing for cellular phones, made secure by their recognition and authorization of a single approved caller. International telephone companies such as Sprint are using similar voice recognition systems. Integrated Speech Solution in Massachusetts is investigating speech applications which can take orders for mutual funds prospectuses and account activities (239). Optical Character Recognition Another potential area for transaction security is in the identification of handwriting by optical character recognition systems (OCR). In conventional OCR systems the program matches each letter in a scanned document with a pre-arranged template st...
