Speech recognition using peak frequency representations

Signal processing for speech recognition combines two distinct elements, spectral estimation, and feature selection. The author separates the issues of estimating the spectrum from that of describing it to a speech recogniser. He focuses on providing a description in terms of the frequencies of peaks. A minimum squared error criterion is used for specifying the description, but it is entirely distinct from that underlying LPC analysis, and is optimised by a dynamic programming technique