“Intelligent” (statistically-guided) algorithms for vowel normalization
Richard A. Harshman, Margaret E. Lundy, Sandra Ferrari Disner · The Journal of the Acoustical Society of America · 1980
New normalization methods are presented which alter a speaker's acoustic space in only “natural” ways, corresponding to identified patterns of naturally occurring speaker variation. These “intelligent” algorithms (i.e., which incorporate statistical-linguistic knowledge) may stretch or shift some regions of a speaker's vowel space more than others, and may do so in directions not parallel to any formant axis. Quantitative descriptions of patterns of speaker variation are obtained by an improved application of PARAFAC three-way factor analysis. Then the investigator selects those factors of variation he wishes to remove and inputs them into the program, along with the data set to be normalized. The program uses regression methods to remove the identifiable aspects of unwanted variation from each speaker's data. Three-factor normalization reduces within-cluster variance in the Peterson-Barney English data by more than 70%, without causing any shifts of vowel cluster centroids. Thus the method seems to be both more powerful and more selective than previously proposed methods.