Title :
A comparison of several speech-spectra classification methods
Author :
Silverman, Harvey F. ; Dixon, N. Rex
Author_Institution :
IBM Thomas J. Watson Research Center, Yorktown Heights, NY
fDate :
8/1/1976 12:00:00 AM
Abstract :
An important consideration in speech processing involves classification of speech spectra. Several methods for performing this classification are discussed. A number of these were selected for comparative evaluation. Two measures of performance-accuracy and stability-were derived through the use of an automatic performance evaluation system. Over 3000 hand-labeled spectra were used. Of those evaluated, a linearly mean-corrected minimum distance measure, on a 40-point spectral representation with a square (or cube) norm was consistently superior to the other methods.
Keywords :
Acoustic signal processing; Automatic speech recognition; Classification algorithms; Frequency; Performance evaluation; Signal processing algorithms; Speech processing; Stability; Steady-state; Vectors;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
DOI :
10.1109/TASSP.1976.1162814