Method of Determining Reference Spectra Suitable for Labeling Speech in Automatic Speech Recognition Systems
Original Publication Date: 1984-Dec-01
Included in the Prior Art Database: 2005-Feb-05
Using a computed average of the spectra aligned against each phone in the training data, rather than using random reference spectra as the starting point, and adjusting these reference spectra by iterative use of the clustering algorithm, increases overall system effectiveness in a continuous speech recognition system. For each spectrum in the training data the closest reference spectrum is found, and the most common correct/current classification error (expressed as a proportion of the correct phone's occurrence) is calculated. For each spectrum the nearest reference spectrum is found; for each reference spectrum all the training spectra for which that reference spectrum was closest are averaged and used as an adjusted reference spectrum replacing that reference spectrum.