In:
The Journal of the Acoustical Society of America, Acoustical Society of America (ASA), Vol. 44, No. 1_Supplement ( 1968-07-01), p. 386-386
Abstract:
Real-time spectrographic analysis involves processing of spectral outputs as vectors in multidimensional space. To reduce the number of dimensions and eliminate redundancy between channels, a covariance matrix can be derived and the eigenvectors calculated. Correlating the spectral cross sections with as few as three eigenvectors can account for up to 98% of the total variance. Following the theory of Yilmas [H. Yilmas, NASA Contract 12–129, Final Rept. (Dec. 1966)], a real-time display using correlations of the first three eigenvectors has been written for a PDP-1 computer. The display consists of a circle representing a cross section of a cone, and a vector representing cone height. The height represents loudness, as determined by the correlation of the first eigenvector; and the circle is analogous to a vowel circle derived from Eigenvectors 2 and 3, normalized for volume by Eigenvector 1. The display provides effective phoneme separation: display coordinates are useful for automatic phoneme identification. The eigenvectors can be quickly recalculated to accommodate variations in language or speech type.
Type of Medium:
Online Resource
ISSN:
0001-4966
,
1520-8524
Language:
English
Publisher:
Acoustical Society of America (ASA)
Publication Date:
1968
detail.hit.zdb_id:
1461063-2
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