Low-complexity small-vocabulary speech recognition for portable devices

Low-complexity technology is a natural focal point for today's portable devices. Low-complexity increases battery life and facilitates small memory platform implementation. We propose the use of polynomial classifiers for portable speech recognition implementation. Polynomial classifiers have a simple architecture which fits well with modern DSP chips. We demonstrate several novel methods for implementing speech recognition. We describe a novel training technique. We also show a technique for fast scoring and prior normalization. We illustrate some of the properties of the methods on a command-and-control database.