Title :
Experimental evaluation of structural features for a speaker-independent voice recognition system
Author_Institution :
Dept. of Electr. Eng., South Florida Univ., Tampa, FL, USA
Abstract :
A preliminary investigation to evaluate a speaker-independent voice-recognition system based on speaker-invariant feature measurements is presented. The signal is represented as a trajectory in the first-order phase plane, from which a set of features is extracted including uncoded and coded intersection number with the x- and y-axes, respectively. Both nearest-neighbor and K-means clustering are used for classification. The feature set was evaluated for speaker-invariant recognition using an orthographic (written) vowel data. Among the features selected, the uncoded intersection number provided much tighter clustering in the decision space with an error rate of 10% using nearest-neighbor classification.<>
Keywords :
speech recognition; K-means clustering; coded intersection number; feature measurements; first-order phase plane; nearest-neighbor classification; orthographic vowel data; speaker-independent voice recognition system; structural features; uncoded intersection number; written vowel data; Automatic speech recognition; Data mining; Distortion; Equations; Error analysis; Feature extraction; Pattern matching; Signal representations; Speech recognition; Topology;
Conference_Titel :
System Theory, 1988., Proceedings of the Twentieth Southeastern Symposium on
Conference_Location :
Charlotte, NC, USA
Print_ISBN :
0-8186-0847-1
DOI :
10.1109/SSST.1988.17078
