Rutenbar, a professor of electrical and computer engineering at Carnegie Mellon, working jointly with researchers at the <?xml:namespace prefix = st1 ns = “urn:schemas-microsoft-com:office:smarttags” />University of California at Berkeley received a $US1 million grant from the National Science Foundation to move automatic speech recognition from software into hardware. The problem is power—or rather, the lack of it. It takes a very powerful desktop computer to recognize arbitrary speech. “But we can’t put a Pentium in my cell phone, or in a soldier’s helmet, or under a rock in a desert,” explains Rutenbar, “the batteries wouldn’t last 10 minutes.” The goal is to create a radically new and efficient silicon chip architecture that only does speech recognition, but does this 100 to 1,000 times more efficiently than a conventional computer. Importantly Carnegie Mellon researchers pioneered much of today’s successful speech recognition technology. This includes the influential ‘Sphinx’ project, the basis for many of today’s commercial speech recognizers.
“Security applications are the big reason we were chosen for this award,” says Rutenbar. “Imagine if an emergency responder could query a critical online database with voice alone, without returning to a vehicle, in a noisy and dangerous environment. The possibilities are endless.” Researchers plan to unveil speech-recognition chip architecture in two to three years.
