DocumentCode
3001193
Title
On the dimensionality of steady-state vowel normalization
Author
Friedman, David H.
Author_Institution
The MITRE Corporation, Bedford, MA
Volume
11
fYear
1986
fDate
31503
Firstpage
2627
Lastpage
2630
Abstract
Vowel classification is considered from the viewpoint of cluster separation in a vector space, with Mahalanobis distance as the criterion. The number of significant axes of variation needed to characterize each speaker, weighted with respect to cluster separation, is found from actual formant data to be on the order of four, and the potential improvement in separation accountable to structure in the data is estimated at about 3 db by comparison with results for the same procedure applied to random data.
Keywords
Character recognition; Data mining; Density functional theory; Frequency estimation; Shape; Speech recognition; Steady-state;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '86.
Type
conf
DOI
10.1109/ICASSP.1986.1168760
Filename
1168760
Link To Document