Features for the identification of mixed excitation in speech analysis

Features for use in a pattern classification scheme to identify simultaneous periodic and noiselike excitation of a segment of speech are examined. Pattern classification techniques have been applied with considerable success to the problem of classifying a speech segment as voiced or unvoiced. The features that have proven adequate for the voiced/unvoiced decision have not sufficed for the three-way voiced/unvoiced/mixed excitation classification. The incorporation of periodicity measures (e.g. from pitch determination algorithms) into such a pattern classification framework are examined. A variety of features which compare periodicity in different bands of the frequency spectrum are presented.